oldwiki.scinet.utoronto.ca - User contributions [en-gb]

Oldwiki.scinet.utoronto.ca:System Alerts

2017-11-11T17:21:37Z

Mponce: /* System Status */

Oldwiki.scinet.utoronto.ca:System Alerts

2017-11-11T17:20:46Z

Mponce: /* System Status */

Oldwiki.scinet.utoronto.ca:System Alerts

2017-03-15T22:14:31Z

Mponce: /* System Status */

== System Status==

{|
|[[File:up.png|up|link=GPC Quickstart]][[GPC Quickstart|GPC]]
|[[File:up.png|up|link=TCS Quickstart]][[TCS Quickstart|TCS]]
|[[File:up.png|up|link=Sandy]][[Sandy]]
|[[File:up.png|up|link=Gravity]][[Gravity]]
|[[File:up.png|up|link=BGQ]][[BGQ]]
|[[File:up.png|file systems unmounted|]]File System
|-
|[[File:up.png|up|link=P7 Linux Cluster]][[P7 Linux Cluster|P7]]
|[[File:up.png|up|link=P8]][[P8]]
|[[File:up.png|up|link=Knights Landing]][[Knights Landing|KNL]]
|[[File:up.png|up|link=Visualization Nodes]][[Visualization Nodes|Viz]]
|[[File:up.png|up|link=HPSS]][[HPSS]]
|}

 Tue Mar 15 18:00:00 EST 2017 Systems are back online and fully operational.

 Tue Mar 15 16:31:39 EST 2017 Power glitch at data center. Compute nodes went down, bringing them up.

 Sun Mar 5 14:34:11 EST 2017 Globus access to HPSS has been re-enabled.

 Thu Mar 2 9:29:14 EST 2017 GPC jobs are back running.

Thu Mar 2 01:54:57 EST 2017 scratch filesystem went down earlier and most GPC jobs were killed. New GPC jobs are in hold till disk check finished in the morning.

Tue Feb 28 2017 16:00:00 EST The file transfer of users files on the old scratch system to the new scratch system has been completed. The new scratch folders are logically in the same place as before, i.e. /scratch/G/GROUP/USER. Your $SCRATCH environment variable will point to this location when you log in. The project folders have also been moved in the same way. Compute jobs have been released and are starting to run. Let us know if you have any concerns. Thank you for you patience.

Tue Feb 28 2017 10:02:45 EST It could take a few more hours for the scratch migration to finish. We still have a dozen or so users to go. Please check this page from time to time for updates.

Mon Feb 27 2017 10:00:00 EST The old scratch was 99% full. Given the current incident of scratch getting unmounted everywhere, we had little choice but to decide that it is time to initiate the transition to the new scratch file system at this point, instead of performing a roll-out approach that we had planned earlier.

We estimate the transition to the new scratch will take roughly one day, but since we want all users' data on the old scratch system to be available in the new scratch (at the same logical location), the exact duration of the transition depends on the amount of new data to be transferred over.

In the meantime, no jobs will start running on the GPC, Sandy, Gravity or P7.

In addition, $SCRATCH will not be accessible to users during the transition, but you can login to the login and devel nodes. $HOME is not affected.

The current scratch system issue and the scratch transition don't affect the BGQ or TCS anymore (although running jobs on TCS may have stopped this morning), because BGQ and TCS have their own separate scratch file systems. It also does not affect groups whose scratch space is on /scratch2.

Mon Feb 27 2017 7:20:00 EST Scratch file system is down. We are investigating.

Wed Feb 22 2017 16:17:00 EST Globus access to HPSS is currently not operational. We hope to have a resolution for this soon.

Oldwiki.scinet.utoronto.ca:System Alerts

2017-03-15T20:52:06Z

Mponce: /* System Status */

== System Status==

{|
|[[File:up25.png|up|link=GPC Quickstart]][[GPC Quickstart|GPC]]
|[[File:up25.png|up|link=TCS Quickstart]][[TCS Quickstart|TCS]]
|[[File:up25.png|up|link=Sandy]][[Sandy]]
|[[File:up25.png|up|link=Gravity]][[Gravity]]
|[[File:up25.png|up|link=BGQ]][[BGQ]]
|[[File:up75.png|file systems unmounted|]]File System
|-
|[[File:up25.png|up|link=P7 Linux Cluster]][[P7 Linux Cluster|P7]]
|[[File:up25.png|up|link=P8]][[P8]]
|[[File:up25.png|up|link=Knights Landing]][[Knights Landing|KNL]]
|[[File:up25.png|up|link=Visualization Nodes]][[Visualization Nodes|Viz]]
|[[File:up.png|up|link=HPSS]][[HPSS]]
|}

 Tue Mar 15 16:31:39 EST 2017 Power glitch at data center. Compute nodes went down, bringing them up.

 Sun Mar 5 14:34:11 EST 2017 Globus access to HPSS has been re-enabled.

 Thu Mar 2 9:29:14 EST 2017 GPC jobs are back running.

Thu Mar 2 01:54:57 EST 2017 scratch filesystem went down earlier and most GPC jobs were killed. New GPC jobs are in hold till disk check finished in the morning.

Tue Feb 28 2017 16:00:00 EST The file transfer of users files on the old scratch system to the new scratch system has been completed. The new scratch folders are logically in the same place as before, i.e. /scratch/G/GROUP/USER. Your $SCRATCH environment variable will point to this location when you log in. The project folders have also been moved in the same way. Compute jobs have been released and are starting to run. Let us know if you have any concerns. Thank you for you patience.

Tue Feb 28 2017 10:02:45 EST It could take a few more hours for the scratch migration to finish. We still have a dozen or so users to go. Please check this page from time to time for updates.

Mon Feb 27 2017 10:00:00 EST The old scratch was 99% full. Given the current incident of scratch getting unmounted everywhere, we had little choice but to decide that it is time to initiate the transition to the new scratch file system at this point, instead of performing a roll-out approach that we had planned earlier.

We estimate the transition to the new scratch will take roughly one day, but since we want all users' data on the old scratch system to be available in the new scratch (at the same logical location), the exact duration of the transition depends on the amount of new data to be transferred over.

In the meantime, no jobs will start running on the GPC, Sandy, Gravity or P7.

In addition, $SCRATCH will not be accessible to users during the transition, but you can login to the login and devel nodes. $HOME is not affected.

The current scratch system issue and the scratch transition don't affect the BGQ or TCS anymore (although running jobs on TCS may have stopped this morning), because BGQ and TCS have their own separate scratch file systems. It also does not affect groups whose scratch space is on /scratch2.

Mon Feb 27 2017 7:20:00 EST Scratch file system is down. We are investigating.

Wed Feb 22 2017 16:17:00 EST Globus access to HPSS is currently not operational. We hope to have a resolution for this soon.

Oldwiki.scinet.utoronto.ca:System Alerts

2017-03-15T20:51:22Z

Mponce: /* System Status */

== System Status==

{|
|[[File:up50.png|up|link=GPC Quickstart]][[GPC Quickstart|GPC]]
|[[File:up50.png|up|link=TCS Quickstart]][[TCS Quickstart|TCS]]
|[[File:up50.png|up|link=Sandy]][[Sandy]]
|[[File:up50.png|up|link=Gravity]][[Gravity]]
|[[File:up50.png|up|link=BGQ]][[BGQ]]
|[[File:up75.png|file systems unmounted|]]File System
|-
|[[File:up50.png|up|link=P7 Linux Cluster]][[P7 Linux Cluster|P7]]
|[[File:up50.png|up|link=P8]][[P8]]
|[[File:up50.png|up|link=Knights Landing]][[Knights Landing|KNL]]
|[[File:up50.png|up|link=Visualization Nodes]][[Visualization Nodes|Viz]]
|[[File:up.png|up|link=HPSS]][[HPSS]]
|}

 Tue Mar 15 16:31:39 EST 2017 Power glitch at data center. Compute nodes went down, bringing them up.

 Sun Mar 5 14:34:11 EST 2017 Globus access to HPSS has been re-enabled.

 Thu Mar 2 9:29:14 EST 2017 GPC jobs are back running.

Thu Mar 2 01:54:57 EST 2017 scratch filesystem went down earlier and most GPC jobs were killed. New GPC jobs are in hold till disk check finished in the morning.

Tue Feb 28 2017 16:00:00 EST The file transfer of users files on the old scratch system to the new scratch system has been completed. The new scratch folders are logically in the same place as before, i.e. /scratch/G/GROUP/USER. Your $SCRATCH environment variable will point to this location when you log in. The project folders have also been moved in the same way. Compute jobs have been released and are starting to run. Let us know if you have any concerns. Thank you for you patience.

Tue Feb 28 2017 10:02:45 EST It could take a few more hours for the scratch migration to finish. We still have a dozen or so users to go. Please check this page from time to time for updates.

Mon Feb 27 2017 10:00:00 EST The old scratch was 99% full. Given the current incident of scratch getting unmounted everywhere, we had little choice but to decide that it is time to initiate the transition to the new scratch file system at this point, instead of performing a roll-out approach that we had planned earlier.

We estimate the transition to the new scratch will take roughly one day, but since we want all users' data on the old scratch system to be available in the new scratch (at the same logical location), the exact duration of the transition depends on the amount of new data to be transferred over.

In the meantime, no jobs will start running on the GPC, Sandy, Gravity or P7.

In addition, $SCRATCH will not be accessible to users during the transition, but you can login to the login and devel nodes. $HOME is not affected.

The current scratch system issue and the scratch transition don't affect the BGQ or TCS anymore (although running jobs on TCS may have stopped this morning), because BGQ and TCS have their own separate scratch file systems. It also does not affect groups whose scratch space is on /scratch2.

Mon Feb 27 2017 7:20:00 EST Scratch file system is down. We are investigating.

Wed Feb 22 2017 16:17:00 EST Globus access to HPSS is currently not operational. We hope to have a resolution for this soon.

Oldwiki.scinet.utoronto.ca:System Alerts

2017-03-15T20:49:09Z

Mponce: /* System Status */

== System Status==

{|
|[[File:up50.png|up|link=GPC Quickstart]][[GPC Quickstart|GPC]]
|[[File:up50.png|up|link=TCS Quickstart]][[TCS Quickstart|TCS]]
|[[File:up50.png|up|link=Sandy]][[Sandy]]
|[[File:up50.png|up|link=Gravity]][[Gravity]]
|[[File:up50.png|up|link=BGQ]][[BGQ]]
|[[File:up.png|file systems unmounted|]]File System
|-
|[[File:up50.png|up|link=P7 Linux Cluster]][[P7 Linux Cluster|P7]]
|[[File:up50.png|up|link=P8]][[P8]]
|[[File:up50.png|up|link=Knights Landing]][[Knights Landing|KNL]]
|[[File:up50.png|up|link=Visualization Nodes]][[Visualization Nodes|Viz]]
|[[File:up.png|up|link=HPSS]][[HPSS]]
|}

 Tue Mar 15 16:31:39 EST 2017 Power glitch at data center. Compute nodes went down, bringing them up.

 Sun Mar 5 14:34:11 EST 2017 Globus access to HPSS has been re-enabled.

 Thu Mar 2 9:29:14 EST 2017 GPC jobs are back running.

Thu Mar 2 01:54:57 EST 2017 scratch filesystem went down earlier and most GPC jobs were killed. New GPC jobs are in hold till disk check finished in the morning.

Tue Feb 28 2017 16:00:00 EST The file transfer of users files on the old scratch system to the new scratch system has been completed. The new scratch folders are logically in the same place as before, i.e. /scratch/G/GROUP/USER. Your $SCRATCH environment variable will point to this location when you log in. The project folders have also been moved in the same way. Compute jobs have been released and are starting to run. Let us know if you have any concerns. Thank you for you patience.

Tue Feb 28 2017 10:02:45 EST It could take a few more hours for the scratch migration to finish. We still have a dozen or so users to go. Please check this page from time to time for updates.

Mon Feb 27 2017 10:00:00 EST The old scratch was 99% full. Given the current incident of scratch getting unmounted everywhere, we had little choice but to decide that it is time to initiate the transition to the new scratch file system at this point, instead of performing a roll-out approach that we had planned earlier.

We estimate the transition to the new scratch will take roughly one day, but since we want all users' data on the old scratch system to be available in the new scratch (at the same logical location), the exact duration of the transition depends on the amount of new data to be transferred over.

In the meantime, no jobs will start running on the GPC, Sandy, Gravity or P7.

In addition, $SCRATCH will not be accessible to users during the transition, but you can login to the login and devel nodes. $HOME is not affected.

The current scratch system issue and the scratch transition don't affect the BGQ or TCS anymore (although running jobs on TCS may have stopped this morning), because BGQ and TCS have their own separate scratch file systems. It also does not affect groups whose scratch space is on /scratch2.

Mon Feb 27 2017 7:20:00 EST Scratch file system is down. We are investigating.

Wed Feb 22 2017 16:17:00 EST Globus access to HPSS is currently not operational. We hope to have a resolution for this soon.

Oldwiki.scinet.utoronto.ca:System Alerts

2017-03-15T20:47:38Z

Mponce: /* System Status */

== System Status==

{|
|[[File:up.png|up|link=GPC Quickstart]][[GPC Quickstart|GPC]]
|[[File:up.png|up|link=TCS Quickstart]][[TCS Quickstart|TCS]]
|[[File:up.png|up|link=Sandy]][[Sandy]]
|[[File:up.png|up|link=Gravity]][[Gravity]]
|[[File:up.png|up|link=BGQ]][[BGQ]]
|[[File:up.png|file systems unmounted|]]File System
|-
|[[File:up.png|up|link=P7 Linux Cluster]][[P7 Linux Cluster|P7]]
|[[File:up.png|up|link=P8]][[P8]]
|[[File:up.png|up|link=Knights Landing]][[Knights Landing|KNL]]
|[[File:up.png|up|link=Visualization Nodes]][[Visualization Nodes|Viz]]
|[[File:up.png|up|link=HPSS]][[HPSS]]
|}

 Tue Mar 15 16:31:39 EST 2017 Power glitch at data center. Compute nodes went down, bringing them up.

 Sun Mar 5 14:34:11 EST 2017 Globus access to HPSS has been re-enabled.

 Thu Mar 2 9:29:14 EST 2017 GPC jobs are back running.

Thu Mar 2 01:54:57 EST 2017 scratch filesystem went down earlier and most GPC jobs were killed. New GPC jobs are in hold till disk check finished in the morning.

Tue Feb 28 2017 16:00:00 EST The file transfer of users files on the old scratch system to the new scratch system has been completed. The new scratch folders are logically in the same place as before, i.e. /scratch/G/GROUP/USER. Your $SCRATCH environment variable will point to this location when you log in. The project folders have also been moved in the same way. Compute jobs have been released and are starting to run. Let us know if you have any concerns. Thank you for you patience.

Tue Feb 28 2017 10:02:45 EST It could take a few more hours for the scratch migration to finish. We still have a dozen or so users to go. Please check this page from time to time for updates.

Mon Feb 27 2017 10:00:00 EST The old scratch was 99% full. Given the current incident of scratch getting unmounted everywhere, we had little choice but to decide that it is time to initiate the transition to the new scratch file system at this point, instead of performing a roll-out approach that we had planned earlier.

We estimate the transition to the new scratch will take roughly one day, but since we want all users' data on the old scratch system to be available in the new scratch (at the same logical location), the exact duration of the transition depends on the amount of new data to be transferred over.

In the meantime, no jobs will start running on the GPC, Sandy, Gravity or P7.

In addition, $SCRATCH will not be accessible to users during the transition, but you can login to the login and devel nodes. $HOME is not affected.

The current scratch system issue and the scratch transition don't affect the BGQ or TCS anymore (although running jobs on TCS may have stopped this morning), because BGQ and TCS have their own separate scratch file systems. It also does not affect groups whose scratch space is on /scratch2.

Mon Feb 27 2017 7:20:00 EST Scratch file system is down. We are investigating.

Wed Feb 22 2017 16:17:00 EST Globus access to HPSS is currently not operational. We hope to have a resolution for this soon.

User Python virtualenv

2016-11-15T15:10:28Z

Mponce: /* Using Python Virtualenv */

== Using Python Virtualenv ==

Virtual environments (short virtualenv) are a standard in Python to create isolated Python environments. This is useful when certain modules or certain versions of modules are not available in the thee default python environment. First load a python module:

<source lang="bash">
module load intel/13.1.1 python/2.7.5
</source>

Then install virtualenv:

<source lang="bash">
pip install virtualenv --user
</source>

Then create a directory for the virtual environments. One can put an virtual environment anywhere, but this directory structure is recommended:

<source lang="bash">
mkdir ~/.virtualenvs
cd ~/.virtualenvs
</source>

Now we create our first virtualenv called ''myenv'' choose any name you like:

<source lang="bash">
~/.local/bin/virtualenv myenv
</source>

After that we can activate that virtual environment:

<source lang="bash">
source ~/.virtualenvs/myenv/bin/activate
</source>

To go back to the normal python installation simply type "deactivate"
As you are in the virtualenv now you can just type ''pip install <required module>'' to install any module in your virtual environment

===Installing the scientific python suite===

For many scientific codes the packages ''numpy'', ''scipy'', ''matplotlib'', ''pandas'' and ''ipython'' are used. Except ''scipy'' all of these install very simply in a virtualenv using the ''pip install <package name>''.

For installing ''scipy'' we first need to install ''numpy'' and then copy scinet's ''site.cfg'' (contains paths to the required libraries for scipy).
So before doing "pip install scipy" do

<source lang="bash">
cp /scinet/gpc/tools/Python/Python275-shared-intel/lib/python2.7/site-packages/numpy/distutils/site.cfg ~/.virtualenvs/myenv/lib/python2.7/site-packages/numpy/distutils/
</source>

and then just do ''pip install scipy''

Knowledge Base: Tutorials and Manuals

2016-09-22T17:34:29Z

Mponce: /* GPU Computing */

__NOINDEX__
__TOC__
=Training material=

For upcoming classes, see our [https://support.scinet.utoronto.ca/education/ Training and Education website]!
==SciNet Basics==
* [[Media:SciNet_Tutorial.pdf|SciNet User Tutorial]]
* [[SciNet Command Line Utilities]]
* Intro to SciNet May 2014: [http://support.scinet.utoronto.ca/CourseVideo/SciNetIntroMay2014/IntroMay2014.html Video]/[[Media:IntroScinetMay2014.pdf|Slides]]
* SciNet Resources: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_SciNet_Resources/Monday_Morning_SciNet_Resources.mp4 Video]/ [[Media:Monday_Morning_SciNet_Resources.pdf|Slides]]
* [[Essentials]]
* [[FAQ|Frequenty asked questions]]
* [[Ssh]]
* [[GPC_Quickstart|GPC quickstart]]
* [[TCS_Quickstart|TCS quickstart]]
* [[GPU_Devel_Nodes|ARC/GPU quickstart]]
* [[Cell_Devel_Nodes|ARC/Cell quickstart]]
* [[Important .bashrc guidelines]]
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Software_and_Libraries | Software and libraries]]
* [[Installing your own modules]]
* [[Media:SNUGlocalsetup.pdf|User-space modules and packages (April 2011 SNUG TechTalk)]]
* [[Media:HPSS_rationale.pdf|HPSS - SciNet's storage capacity expansion]]
* BGQ Hardware Overview [https://support.scinet.utoronto.ca/~northrup/bgqhardware.pdf Slides ]/ [https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqhardware/bgqhardware.mp4 Video Recording ]
* Intro to Using the BGQ [[Media:Bgqintro.pdf|Slides ]]/[https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqintro/bgqintro.mp4 Video Recording ]

==Linux==
* [http://www.ee.surrey.ac.uk/Teaching/Unix/index.html Linux Tutorial] (warning: the last part of this tutorial is specific to the csh shell, whereas SciNet uses the bash shell).
* Linux Command Line: A Primer (June 2012) [[Media:SS_IntroToShell.pdf|Slides,]] [[Media:SS_IntroToShell.tgz|Files]]
* Introduction to the Linux Shell, SciNet, Mar 2012: [[Media:IntroToShell.pdf|Slides]] and [[Media:Shell-data.tgz|Data files]]

==Batch job management==
* [https://support.scinet.utoronto.ca/education/go.php/183/file_storage/index.php/download/1/files%5B%5D/3702/ Job and Queue Management Tools] (Techtalk Mar.11, 2015)
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (Techtalk Nov 14, 2012)]]
* [[Media:TechTalkJobMonitoring.pdf|Job Monitoring on SciNet and Job Efficiency]]

* [[Wallclock time]]
* [[Checkpoints]]
* [[Using_Signals|Signals]]
* [[Moab]]
* [[User_Serial|Serial Jobs (including GNU Parallel)]]
* [[User_Ramdisk|Ramdisk]]
* [http://www.clusterresources.com/products/mwm/docs/index.shtml Moab workload manager]
* [http://www.clusterresources.com/products/mwm/docs/a.gcommandoverview.shtml Moab commands]
* [http://www.clusterresources.com/products/torque/docs/ Torque resource manager]
* [http://www.clusterresources.com/products/torque/docs/a.acommands.shtml Torque PBS commands]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==Programming==
===General===
* [[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers]]: Slides fromt the SciNet Develop Seminar by Kit Barton, Sep 17, 2012.
* [[Media:Remotescinet.pdf‎|Remote Development]], slides from TechTalk Jun 13, 2012
* [[Scientific Software Development Course]], part I of the SciNet's Scientific Computing Course
* [http://software-carpentry.org Software Carpentry Resources]
* Version Control: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_BP_Revision_Control/Thursday_Morning_BP_Revision_Control.mp4 Video]/ [[Media:Snug_techtalk_revcontrol.pdf | Slides]]
* [[IBM_Nov_Workshop | IBM AIX Workshop, SciNet, Nov 2008 ]]
* [[IBM_Compiler_Workshop | IBM Compiler Workshop, SciNet, Feb 2009]]
* SNUG Techtalk Dec 2011 [[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations]]

===Fortran===
* Modern Fortran Course (1 day), SciNet, 19 Apr 2011
** [[Media:ModernFortran.pdf | Slides]]
** [[Media:ModernFortran.tgz | Source Code]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerp* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf IBM Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]

===C++===
* [[Media:Cpp11.pdf|Slides]] and [http://support.scinet.utoronto.ca/CourseVideo/Cpp11/cpp11.html recording] of the SciNet Developer Seminar on C++11, March 20, 2013
* Scientific C++ Course (1 day), SciNet, 15 March 2011
** [[Media:Scientific-c%2B%2B.pdf|Slides]] (updated on Apr 26, 2012)
** [[Media:Scinetcppexamples.tgz|Example source code]]
** [[Videos_of_the_One-Day_Scientific_C%2B%2B_Class | Videos of the Scientific C++ class]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerpro/en-us/cpp/lin/compiler_c/index.htm Intel C & C++ compiler]
ro/en-us/fortran/lin/compiler_f/index.htm Intel Fortran compiler]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf IBM C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]

===C===
* C refresher: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_C_Review/Monday_Morning_C_Review.mp4 Video]/ [[Media:Monday_Morning_C_Review.pdf| Slides]]
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf IBM C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]

===Cilk Plus===
* [[Media:TechTalkSzalwinskiCilkPlus.pdf|CilkPlus - Getting Started]] (slides of the May 2014 TechTalk by Chris Szalwinski)

===Hadoop===
* Introduction to Hadoop for HPCers, Part I - MapReduce: [[Media:Hadoop-PartI.pdf|Slides]], [[Media:HadoopPart1examples.tgz|Source Code]], [http://support.scinet.utoronto.ca/~ljdursi/SciNetHadoopVM.zip Virtual Machine]

===Perl===
* [[Perl]]
===Python===
* [[Python]]
* [[IPython Notebook on GPC]] (January 2014 TechTalk)
* [[Research Computing with Python]] (Modular Course, Fall 2013)
* [[Intro to Tkinter|Python GUIs with Python and TkInter]] [[Media:Tkinter.pdf|slides]] [[Media:Tkinter_code.tgz|code]]
* [http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html f2py: Fortran and Python] (June 2011 TechTalk by Pierre de Buyl)

===R===
* [[R Statistical Package]]
===Lua===
* [[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind]] (May 2011 TechTalk by Peter Colberg)

==Parallel Programming==
* [[2014 Ontario Summerschool on High Performance Computing Central]] (incl. OpenMP and MPI)
* [[High Performance Scientific Computing Course 2014]] (OpenMP and MPI, with video recordings of lectures)
* [[Media:SciNet_MPI3.0_seminar.pdf | MPI 3 Developer Seminar]]
* [[Media:Ds-openmp.pdf| OpenMP 4 Developer Seminar]]
* [[Ontario Summerschool on High Performance Computing Central]] (2013)
* [[High Performance Scientific Computing]], part 3 of SciNet's Scientific Computing Course (Winter 2012)
* Parallel Programming Course (5 days), SciNet, May 2011
** [[Parallel_Scientific_Computing_-_May_2011 | Videos, slides and code]]
* Parallel Computing for Computational Fluid Dynamics (CFD), SciNet, 23 March 2011
** [[Media:parCFD-mpi.pdf | Slides]]
** [[Media:parCFD.tgz | Source Code]]
* Intro to Practical Parallel Programming (1 day), SciNet, 22 Sept 2010:
**[[Media:PPP-Intro-Morning.pdf|Morning Slides, Intro and OpenMP ]]
**[[Media:PPP-Intro-Afternoon.pdf|Afternoon Slides, MPI]]
**[[Media:Intro-ppp.tgz|Example source code]]
* Parallel Scientific Computing Workshop (5 days), SciNet, Aug 2009:
**[[ Parallel_Scientific_Computing_-_Aug_09 | Slides ]]
**[http://www.cita.utoronto.ca/~ljdursi/PSP/ Video]
* [http://www.vscse.org/ Virtual School for CSE] Web courses (Jul/Aug 2010):
** Petascale programming environments and tools
** Big data for science
** Proven algorithmic techniques for many-core processors
* [https://computing.llnl.gov/tutorials/mpi/ LLNL MPI Tutorial]: This was the basis for the MPI workshop at SciNet.
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [[GPC MPI Versions]]
* [[Co-array Fortran on the GPC]]
* [[IBM_Feb_Workshop | IBM MPI Workshop, SciNet, Feb 2009]]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf IBM UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]

==GPU Computing==
* 1-day "Introduction to GPGPU Programming with CUDA" Course (May 2015): [https://support.scinet.utoronto.ca/education/go.php/251/index.php/ib/1//p_course/251].
* 2-day "Programming GPUs with CUDA" Course (2015 Summer School): [https://wiki.scinet.utoronto.ca/wiki/index.php/2015_Ontario_Summer_School_for_High_Performance_Computing_Central#Programming_GPUs_with_CUDA]
* [[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]
* [[Media:Westgrid_CUDA.pdf | Intro to GPU Computing Using CUDA]] (WestGrid Spring 2014 Seminar Series)
* 1.5 hour intro to CUDA, March 2013: [[Media:CUDA-Graphics-Intro-2013.pdf | Slides]] and [[Media:CUDA-Graphics-Intro-2013.tgz | Source Code]]
* [[CUDA_Minicourse_Fall_2012 | CITA/SciNet CUDA Minicourse, Fall 2012]]
* [[SciNet GPU Workshop July 2010]]
* Intro to GPGPU Programming: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_GPGPU/Friday_Morning_GPGPU.mp4 Video]/ [[Media:Gpgpu.pdf | Slides]] (from 5 day parallel programming course at SciNet, May 2011)
* 1-day intro to GPGPU using CUDA Course (Aug 2011): [[Media:Intro-gpu.tgz | Source Code]], [[Media:IntroGPGPU-Aug2011.pdf | Slides]].
* [http://developer.nvidia.com/object/cuda_training.html NVidia archived courses for GPGPU Programming]
* [http://www.pgroup.com/doc/pgiug.pdf PGI Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf PGI Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf PGI Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf PGI CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf PGI OpenACC Getting Started Guide]

==Performance Tuning==
* [[Performance and Profiling Course, April 2013]]
* [[Introduction To Performance]]
* Performance tools for [[Performance_And_Debugging_Tools:_GPC | GPC ]] and [[Performance_And_Debugging_Tools:_TCS | TCS ]]
* Dec 2010 SNUG TechTalk: [[Media:ProfillingTechTalk-Dec2010.pdf | Profiling Tools on GPC]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters]] - SNUG TechTalk, Feb 2012
* [http://cnx.org/content/col11136/latest/ High Performance Computing Book] Online version of an older O'Reilly book which covers the basics of (mostly serial) programming for performance. Covers the most important issues today (such as cache) very clearly.
* [http://www.ece.cmu.edu/~franzf/papers/gttse07.pdf How to Write Fast Numerical Code ] Good introduction to thinking about performance and cache.

==Debugging==
* [[Parallel Debugging with DDT]]
* [[Media:SS_Debug.pdf|Debugging with GDB and DDT, half-day session at the Ontario HPC Summerschool 2012 Central Slides]], [[Media:SS_Debug.tgz|Code]].
* [[Media:Snugdebug.pdf|TechTalk: Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb], SciNet User Group Meeting, Nov 2010]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_Debugging/Thursday_Morning_Debugging.mp4 Video]
* [http://www.allinea.com/downloads/userguide.pdf Allinea DDT (Distributed Debugging Tool) User Guide]

==Math libraries (BLAS, LAPACK, FFT)==
* [[Media:MKLTechTalkMarch2012.pdf|Intel Math Kernel Library (MKL): An overview]] (TechTalk, March, 2012)
* [[Numerical Tools for Physical Scientists]], part 2 of SciNet's Scientific computing course, covers, random nubers, blas, lapack, fft, ...
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf Parallel ESSL high performance math library V3.3]
* [http://hal.inria.fr/inria-00576469 Linear Algebra Libraries] by Claire Mouton. 2009 INRIA Technical Report on existing linear algebra libraries for C++ (also here: [http://arxiv.org/abs/1103.3020])

==I/O==

* [[Media:NetCDF.pdf|Introduction to NetCDF4 binary files with Python, C++ and R (TechTalk March 2014)]]
* [[Using MySQL on the GPC]]
* [https://support.scinet.utoronto.ca/education/go.php/19/content.php/cid/59/ Relational Database Basics]
* [[Media:SCIENCEDATA.pdf‎|Sep 2012 SNUG TechTalk: Science=Data]]
* [[Data_Management|Data management]]
* Intro to Parallel I/O, SciNet, Oct 6th, 2010:
**[[Media:Parallel_io_course.pdf‎|Morning & MPI-IO Slides]]
**[[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
**[[Media:ParIO.tgz|Source Code]].
* Intro to Parallel I/O, SciNet, Feb, 2013
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-intro/pario-intro.mp4 Video of the Introduction]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-netcdfhdf5/pario-netcdfhdf5.mp4 Video of the parallel hdf5 and netcdf part] [[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-mpiio/pario-mpiio.mp4 Video of the MPI-IO part]
* Half-day HPCS2012 Parallel I/O tutorial, covering MPI-IO, HDF5, NetCDF, based on the above: [[Media:ParIO-HPCS2012.pdf|slides (pdf)]] and [[Media:ParIO-HPCS2012.tgz|source code]].
* [[Media:Snugio.pdf|Sept 2010 SNUG TechTalk: Parallel File System and IO]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_IO/Friday_Morning_IO.mp4 Video]
* [[File System and I/O dos and don'ts]]
* [[Media:40TB.pdf|So you have 40TB of Data]] -- an overview of things to consider with large data sets.
* [[Media:Adios-techtalk-may2012.pdf|May 2012 SNUG TechTalk: ADIOS for Parallel IO slides]] and [[Media:Adios-techtalk-may2012-src.tgz|source code]]
* [[hdf5_table|Writting / Reading a table in hdf5]]
* [[NetCDF_table|Writting / Reading a table in NetCDF]]
* Intro to Parallel I/O, SciNet, Sept 215
** MPI-IO [[Media:ParIO.MPIIO.2015.pdf |Slides]] and [[Media:ParIO.MPIIO.tar.gz | Sample codes]]
** [[Media:netcdf2015.pdf | NETCDF]] & [[Media:hfd5.pdf | HDF5]]

==Infiniband Networking==
* [[Media:Snug_techtalk_Infiniband.pdf | TechTalk on SciNet's Infiniband Network & MPI options ]]

==Visualization==
* [[Using Paraview]]
* [[VNC|VNC on the GPC]] (see also [[Media:Ttvnc.pdf|slides of the TechTalk on VNC]])
* [[Software_and_Libraries#anchor_viz|Visualization Software on the GPC]]
* [https://wiki.scinet.utoronto.ca/wiki/images/5/51/Remoteviz.pdf Remote visualization (X-forwarding and VNC)]
* [[Using Paraview]]
* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf gnuplot, xmgrace, remote visualization tools (X-forwarding and VNC), python's matplotlib]
* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Brief overview of ParaView & VisIt]
* [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ VisIt Basics]
* [https://support.scinet.utoronto.ca/education/go.php/273/file_storage/index.php/download/1/files%5B%5D/7363/ Scientific Visualization using VisIt (Basics and Advanced)], M.Ponce and A.Razoumov
* [https://support.scinet.utoronto.ca/education/get.php/8_ComplexNetworks.pdf Intro to Complex Networks Visualization, with Python]

* [http://scienceillustrated.ca Science Illustrated:] Two-day symposium on Visualizing Science, Feb 2011
* [http://www.kmdi.utoronto.ca/story/2011/03/si-science-illustrated-symposium-success Videos of the talks given at Science Illustrated] (recorded by [http://www.kmdi.utoronto.ca KMDI] at [http://www.utoronto.ca UoT]):
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=94ff5cd5-be6e-4fc6-9be6-dd2222342bcd Opening remarks] by Paul Young
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4255c34e-15e7-4b24-ba99-78f5c8fa4381 Information Visualization and the Myth of Information Overload] by Christopher Collins
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=adcf02bf-16cb-46cc-8cdc-1a65e9071d6b Beyond Basic Visualization] by Ramses Van Zon
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=47baf346-3599-4fa3-9b10-6a58faa6b33c Network Visualization & Analysis] by Igor Jurisica
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7e754a2e-7be5-476e-bb54-37def37bc07e Simulation and Visualization of Blood Flow] by David Steinman
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=d7622587-2c31-49c1-99d7-f0f16c078801 Scientific Visualizations: Does the Science Matter?] by Thomas Lucas
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=9963c637-6840-454f-a57f-9a1be6456616 How can visualization impact public perception of science?] Panelists: Jay Ingram, Peter Calamai, Reni Barlow, Hooley McLaughlin
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=88e50cff-db9b-4c71-b10d-781fec60a2c0 How Info Graphics are Created for the Mainstream Media] by Peter Calamai
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=3897e2a3-1fda-42be-ab78-edbab090fd9e Design Boot Camp] by Graham Huber
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4c27ed76-7292-407e-83a6-814e1461eccd Visualization Large Datasets] by Jonathan Dursi
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d49c845-3937-44e2-a300-9b8ffe57a857 Visualizing Colliding Black Holes] by Herald Pfeiffer
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d7e4803-39cd-4c8e-a443-bc2a7b1b3c28 Closing remarks] by Mubdi Rahman

==Applications==
{{:Knowledge Base: Applications}}
* See also [[User Codes]]

=Manuals=

==Intel compilers and libraries (GPC)==
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/cpp-lin/index.htm C & C++ compiler]
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/fortran-lin/index.htm Fortran compiler]
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [[Media:Compiler_qrg12.pdf‎|Intel Compiler Optimization Guide]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)

==IBM compilers and libraries (TCS/P7)==
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [[Media:essl51.pdf|ESSL high performance math library V5.1 for Linux on Power]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==PGI compilers (ARC)==
* [http://www.pgroup.com/doc/pgiug.pdf Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf OpenACC Getting Started Guide] (Note: $PGI/linux86-64/12.5/doc contains a newer version.)

==Scheduler (Adaptive Computing/Cluster Resources)==
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/help.htm Moab workload manager]
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/Content/a.gcommandoverview.html Moab commands]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm Torque resource manager]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm#topics/12-appendices/commandsOverview.htm Torque PBS commands]

==DDT Debugger (Allinea)==
* [http://www.allinea.com/downloads/userguide.pdf Distributed Debugging Tool User Guide]

SciNet TechTalks and Seminars

2016-09-19T21:15:11Z

Mponce: /* Sept 14, 2016, SNUG TechTalk */

__NOTOC__
The SciNet Users Group (SNUG) meetings are every month on the second Wednesday, and involve pizza, user discussion, feedback, and a TechTalk or two (half-hour talk or two 15 minutes talks) on topics or technologies of interest to the SciNet community.

The pdfs of these TechTalks can be found here on the wiki. Below is a chronological list. Most pdfs can also be found on the [[Knowledge Base: Tutorials and Manuals |
Tutorials and manuals page]] which is ordered by topic.

== Sept 14, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet, UofT) 
[[Media:Viz-tools_overview_SNUG-sept2016.pdf‎ | Overview of 3D Scientific Visualization Tools]]

== Jun 8, 2016, SNUG TechTalk==
* Michael Wong (Codeplay/Canadian Head of Delegation to the C++ Standard) C++17: Will it be great or just OK?

== May 11, 2016, SNUG TechTalk==
* Jon Pipitone (CAMH) [https://support.scinet.utoronto.ca/education/get.php/qbatch.pdf qbatch - a tool for executing commands in parallel on clusters]

== Apr 13, 2016, SNUG TechTalk==
* AJ Guillon (Yetiware Inc.) Bewitched, Bothered and Bewildered: Parallelism and Memory Modules

== Feb 10, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ Scientific Visualization, an overview of VisIt]''' [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6400/ data]

== Dec 9, 2015, SNUG TechTalk ==
* Ramses van Zon (SciNet) [[Media:lmodtt.pdf|LMOD: a hierarchical system for software modules]]

== Nov 25, 2015: Seminar==
* Andre Recnik (University of Toronto) '''[[Media:missing.pdf|The CHIME X-Engine: A 7 PetaOP supercomputer with a 6.5 Tb/s network]]'''

== Oct 14, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:remoteviz.pdf|Remote graphics on the GPC: client-server application and VNC]]'''

== Sept 9, 2015: SNUG TechTalk==
* Leslie Barnes and Dylanne Dearborn (UoT) '''[[Media:ttdatamanagement.pdf|Research Data Management: A Brief Introduction]]'''

== Jun 10, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttrarray.pdf|Multidimensional Arrays in C++: rarrays]]'''

== Apr 8, 2015: SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/Snug/sph/mponce-sph_SNUG-apr2015.pdf Smoothed Particle Hydrodynamics: Applications to Astrophysical Simulations ]'''

== Mar 11, 2015: SNUG TechTalk==
* Mike Nolta (SciNet) '''[[Media:20150311-snug-newtools.pdf| Job and Queue Management ]]'''

== Feb 11, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttdata.pdf| Data Management and Transfer Tools at SciNet]]'''

== Nov 19, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]'''

== Oct 8, 2014: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''PyTables: Large Data and HDF5 in Python'''

== Sept 10, 2014: SNUG TechTalk==
* Jason Chong (SciNet) '''Globus'''

== May 14, 2014: SNUG TechTalk==
* Chris Szalwinski (Seneca College) '''[[Media:TechTalkSzalwinskiCilkPlus.pdf| Getting Started with Cilk Plus]]'''

== Apr 9, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snug_ish.pdf| Keep inventory of your data on different file systems with ISH]]'''

== Mar 12, 2014: SNUG TechTalk==
* Bertrand Brelier (IBM@SciNet) '''[[Media:NetCDF.pdf| Introduction to NetCDF4 binary files with Python, C++ and R]]'''

== Feb 12, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_XeonPhi.pdf| Introduction to the Xeon Phi]]'''

== Jan 15, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[IPython Notebook on GPC]]'''

== Dec 11, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttsystems.pdf|New and Existing Resources Available at SciNet]]'''

== Nov 13, 2013: SNUG TechTalk==
* Peter Colberg (SciNet) '''Self-propelled dimer motors: Small-code large-scale simulations using OpenCL and LuaJIT'''

== Oct 16, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Using MySQL on the GPC]]'''

== Sep 11, 2013: SNUG TechTalk==

* Peter Colberg (Chemistry, University of Toronto) '''[https://support.scinet.utoronto.ca/education/go.php/15/content.php/cid/18 Git-annex or: How I learned to stop worrying and manage the data]'''

== May 1, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:TechTalkJobMonitoring.pdf| Monitoring jobs at SciNet (slides)]]'''

== April 10, 2013: SNUG TechTalk==
* Scott Zuyderduyn (Bader Lab, U. of Toronto) '''Using GPUs to Model Higher-Dimensional Influences in Biological Networks'''

== Mar 13, 2013: SNUG TechTalk==
* Deepak Chandan (Phyics, University of Toronto) '''[[Media:TechTalkChandanSparseMKL.pdf| Using sparse matrices and solver routines from the Intel Math Kernel Library (slides)]]'''

== Feb 13, 2013: SNUG TechTalk==
* Ramses van Zon/Jaime Pinto (SciNet) '''[[Media:Hpss-TechTalkFeb2013.pdf|Demystifying HPSS (slides)]]'''

== Jan 9, 2013: SNUG TechTalk==
* Christopher Ing (Pomès Lab, Hospital for Sick Children, Toronto) '''[[Media:SNUG_Jan9.pdf|Interactive Computational Biology (slides)]]'''

==Dec 12, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Ttvnc.pdf|Faster remote graphical interfaces with VNC (slides)]]'''

==Nov 27, 2012: SciNet Bioinformatics Seminar==
* Sébastien Boisvert and Élénie Godzaridis (Laval) '''[[Media:BoisvertGodzaridis-presentation-for-biologists-and-bioinformaticians.pdf‎‎|Massively parallel assemblers for massively parallel DNA sequencers (slides)]]'''

==Nov 26, 2012: SciNet Developer Seminar==
*Élénie Godzaridis, Sébastien Boisvert (Laval) '''[[Media:GodzaridisBoisvert-presentation-for-computer-scientists.pdf|Granularities and messages: from design to abstraction to implementation to virtualization (slides)]]'''

==Nov 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (slides)]]'''

==Oct 24, 2012: SciNet Developer Seminar==
* Mark Ebersole (NVIDIA) '''[[Media:SciDevOpenACC.pdf|OpenACC (slides)]]'''

==Oct 23, 2012: SciNet Developer Seminar==
* Michael Nolta (CITA, Toronto) '''[[Media:Scinet_julia.pdf|The Julia Language (slides)]]'''

== Oct 10, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_BGQ.pdf|SciNet BlueGene/Q (slides)]]'''

== Oct 3, 2012: SciNet Developer Seminar==
* Kit Barton (IBM) '''[[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers (slides)]]'''

== Sep 12, 2012: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:SCIENCEDATA.pdf|Science is Data (slides)]]'''

==Jun 13, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Remotescinet.pdf | Remote development on SciNet (slides)]]'''

==May 9, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Adios-techtalk-may2012.pdf|ADIOS for Parallel IO (slides)]]''' [[Media:Adios-techtalk-may2012-src.tgz|source code]]

==Apr 11, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_Infiniband.pdf | SciNet's Infiniband Network & MPI options (slides)]]'''

==March 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:MKLTechTalkMarch2012.pdf | Intel Math Kernel Library (slides)]]'''

==February 8, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters (slides)]]'''

==January 11, 2012: SNUG TechTalk==
* Chris Neale, Pawel Pomorski, Nilmadhab Chakrabarti, Emil F. Pai, Régis Pomès (Sick Children's Hospital) '''Kinetics of Hydrophobic Gating and Energetics of Magnesium Permeation in the Bacterial Divalent Cation Transport System CorA'''

==December 14, 2011: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations (slides)]]'''

==November 9, 2011: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snugtt2.pdf | How to deal with the new file system setup at SciNet (slides)]]'''

==October 12, 2011: SNUG TechTalk==
* Manuel Saldaña (Arch Es Computing) '''[[Media:ArchES-MPI-at-scinet2011.pdf | MPI as a programming model for High-Performance Reconfigurable Computers (slides)]]'''

==September 14, 2011: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:HPSS_rationale.pdf‎ | HPSS - SciNet's Storage Capacity Expansion (slides)]]'''

==June 8, 2011: SNUG TechTalk==
* Pierre de Buyl (CPTG Toronto/ULB Brussels) '''[http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html Fortran and Python (slides)]'''

==May 4, 2011: SNUG TechTalk==
* Peter Colberg (CPTG, Toronto) '''[[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind (slides)]]'''

==April 12, 2011: SNUG TechTalk==
* Rames van Zon (SciNet) '''[[Media:SNUGlocalsetup.pdf | User-Space Modules and Packages on SciNet (slides)]]'''

==March 9, 2011: SNUG TechTalks==
* Abdul Mroue (CITA, Toronto) '''[[Media:Mroue_SNUG_March_2011.pdf | Precessing Binary Black Hole Simulations (slides)]]'''
* Joachim Harnois-Déraps (CITA, Toronto) '''[[Media:Harnois_SNUG_March_2011.pdf | Weak Gravitational Lensing (slides)]]'''

==February 9, 2011: SNUG TechTalk==
* Seth Dworkin (Mechanical and Industrial Engineering, UoT) '''[[Media:SNUG_seminar_Feb_2011.pps | Computational Combustion: Toward the use of Sustainable and Alternative Fuels (slides)]]'''
* Ramses van Zon (SciNet) '''[[Media:Snugtrackjob.pdf | Job Monitoring on SciNet and Job Efficiency (slides)]]'''

==January 12, 2011: SNUG TechTalks==

* Sarah Rauscher (Regis Pomes group, Sick Kids, Toronto) '''[[Media:Rauscher_SNUG_Tech_Talk_Jan_12_2011.pdf | MD Simulations of Biomolecular Systems (slides)]]'''
* Bijia Pang (Ue-Li Pen group, CITA, UoT) '''[[Media:BPang_SNUG_Tech_Talk_Jan_12_2011.pdf | Black Hole Accretion on 17576 CPUs (slides)]]'''

==December 8, 2010: SNUG TechTalk==

* Jonathan Dursi (SciNet) '''[[Media:ProfillingTechTalk-Dec2010.pdf | Profiling and Tuning (slides)]]'''

==November 10, 2010: SNUG TechTalk ==

* Ramses van Zon (SciNet) '''[[Media:Snugdebug.pdf | Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb (slides)]]'''

==October 13, 2010: SNUG TechTalk==

* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_revcontrol.pdf|Version Control (slides)]]'''

==September 8, 2010: SNUG TechTalk==

* Ramses van Zon (SciNet) '''[[Media:Snugio.pdf | The Parallel File System and I/O (slides)]]'''

File:Viz-tools overview SNUG-sept2016.pdf

2016-09-19T21:12:26Z

Mponce:

SciNet TechTalks and Seminars

2016-09-19T21:11:18Z

Mponce: /* Sept 14, 2016, SNUG TechTalk */

__NOTOC__
The SciNet Users Group (SNUG) meetings are every month on the second Wednesday, and involve pizza, user discussion, feedback, and a TechTalk or two (half-hour talk or two 15 minutes talks) on topics or technologies of interest to the SciNet community.

The pdfs of these TechTalks can be found here on the wiki. Below is a chronological list. Most pdfs can also be found on the [[Knowledge Base: Tutorials and Manuals |
Tutorials and manuals page]] which is ordered by topic.

== Sept 14, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet, UofT) 
[[Media:Viz-tools_overview.pdf | Overview of 3D Scientific Visualization Tools]]

== Jun 8, 2016, SNUG TechTalk==
* Michael Wong (Codeplay/Canadian Head of Delegation to the C++ Standard) C++17: Will it be great or just OK?

== May 11, 2016, SNUG TechTalk==
* Jon Pipitone (CAMH) [https://support.scinet.utoronto.ca/education/get.php/qbatch.pdf qbatch - a tool for executing commands in parallel on clusters]

== Apr 13, 2016, SNUG TechTalk==
* AJ Guillon (Yetiware Inc.) Bewitched, Bothered and Bewildered: Parallelism and Memory Modules

== Feb 10, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ Scientific Visualization, an overview of VisIt]''' [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6400/ data]

== Dec 9, 2015, SNUG TechTalk ==
* Ramses van Zon (SciNet) [[Media:lmodtt.pdf|LMOD: a hierarchical system for software modules]]

== Nov 25, 2015: Seminar==
* Andre Recnik (University of Toronto) '''[[Media:missing.pdf|The CHIME X-Engine: A 7 PetaOP supercomputer with a 6.5 Tb/s network]]'''

== Oct 14, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:remoteviz.pdf|Remote graphics on the GPC: client-server application and VNC]]'''

== Sept 9, 2015: SNUG TechTalk==
* Leslie Barnes and Dylanne Dearborn (UoT) '''[[Media:ttdatamanagement.pdf|Research Data Management: A Brief Introduction]]'''

== Jun 10, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttrarray.pdf|Multidimensional Arrays in C++: rarrays]]'''

== Apr 8, 2015: SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/Snug/sph/mponce-sph_SNUG-apr2015.pdf Smoothed Particle Hydrodynamics: Applications to Astrophysical Simulations ]'''

== Mar 11, 2015: SNUG TechTalk==
* Mike Nolta (SciNet) '''[[Media:20150311-snug-newtools.pdf| Job and Queue Management ]]'''

== Feb 11, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttdata.pdf| Data Management and Transfer Tools at SciNet]]'''

== Nov 19, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]'''

== Oct 8, 2014: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''PyTables: Large Data and HDF5 in Python'''

== Sept 10, 2014: SNUG TechTalk==
* Jason Chong (SciNet) '''Globus'''

== May 14, 2014: SNUG TechTalk==
* Chris Szalwinski (Seneca College) '''[[Media:TechTalkSzalwinskiCilkPlus.pdf| Getting Started with Cilk Plus]]'''

== Apr 9, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snug_ish.pdf| Keep inventory of your data on different file systems with ISH]]'''

== Mar 12, 2014: SNUG TechTalk==
* Bertrand Brelier (IBM@SciNet) '''[[Media:NetCDF.pdf| Introduction to NetCDF4 binary files with Python, C++ and R]]'''

== Feb 12, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_XeonPhi.pdf| Introduction to the Xeon Phi]]'''

== Jan 15, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[IPython Notebook on GPC]]'''

== Dec 11, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttsystems.pdf|New and Existing Resources Available at SciNet]]'''

== Nov 13, 2013: SNUG TechTalk==
* Peter Colberg (SciNet) '''Self-propelled dimer motors: Small-code large-scale simulations using OpenCL and LuaJIT'''

== Oct 16, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Using MySQL on the GPC]]'''

== Sep 11, 2013: SNUG TechTalk==

* Peter Colberg (Chemistry, University of Toronto) '''[https://support.scinet.utoronto.ca/education/go.php/15/content.php/cid/18 Git-annex or: How I learned to stop worrying and manage the data]'''

== May 1, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:TechTalkJobMonitoring.pdf| Monitoring jobs at SciNet (slides)]]'''

== April 10, 2013: SNUG TechTalk==
* Scott Zuyderduyn (Bader Lab, U. of Toronto) '''Using GPUs to Model Higher-Dimensional Influences in Biological Networks'''

== Mar 13, 2013: SNUG TechTalk==
* Deepak Chandan (Phyics, University of Toronto) '''[[Media:TechTalkChandanSparseMKL.pdf| Using sparse matrices and solver routines from the Intel Math Kernel Library (slides)]]'''

== Feb 13, 2013: SNUG TechTalk==
* Ramses van Zon/Jaime Pinto (SciNet) '''[[Media:Hpss-TechTalkFeb2013.pdf|Demystifying HPSS (slides)]]'''

== Jan 9, 2013: SNUG TechTalk==
* Christopher Ing (Pomès Lab, Hospital for Sick Children, Toronto) '''[[Media:SNUG_Jan9.pdf|Interactive Computational Biology (slides)]]'''

==Dec 12, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Ttvnc.pdf|Faster remote graphical interfaces with VNC (slides)]]'''

==Nov 27, 2012: SciNet Bioinformatics Seminar==
* Sébastien Boisvert and Élénie Godzaridis (Laval) '''[[Media:BoisvertGodzaridis-presentation-for-biologists-and-bioinformaticians.pdf‎‎|Massively parallel assemblers for massively parallel DNA sequencers (slides)]]'''

==Nov 26, 2012: SciNet Developer Seminar==
*Élénie Godzaridis, Sébastien Boisvert (Laval) '''[[Media:GodzaridisBoisvert-presentation-for-computer-scientists.pdf|Granularities and messages: from design to abstraction to implementation to virtualization (slides)]]'''

==Nov 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (slides)]]'''

==Oct 24, 2012: SciNet Developer Seminar==
* Mark Ebersole (NVIDIA) '''[[Media:SciDevOpenACC.pdf|OpenACC (slides)]]'''

==Oct 23, 2012: SciNet Developer Seminar==
* Michael Nolta (CITA, Toronto) '''[[Media:Scinet_julia.pdf|The Julia Language (slides)]]'''

== Oct 10, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_BGQ.pdf|SciNet BlueGene/Q (slides)]]'''

== Oct 3, 2012: SciNet Developer Seminar==
* Kit Barton (IBM) '''[[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers (slides)]]'''

== Sep 12, 2012: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:SCIENCEDATA.pdf|Science is Data (slides)]]'''

==Jun 13, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Remotescinet.pdf | Remote development on SciNet (slides)]]'''

==May 9, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Adios-techtalk-may2012.pdf|ADIOS for Parallel IO (slides)]]''' [[Media:Adios-techtalk-may2012-src.tgz|source code]]

==Apr 11, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_Infiniband.pdf | SciNet's Infiniband Network & MPI options (slides)]]'''

==March 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:MKLTechTalkMarch2012.pdf | Intel Math Kernel Library (slides)]]'''

==February 8, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters (slides)]]'''

==January 11, 2012: SNUG TechTalk==
* Chris Neale, Pawel Pomorski, Nilmadhab Chakrabarti, Emil F. Pai, Régis Pomès (Sick Children's Hospital) '''Kinetics of Hydrophobic Gating and Energetics of Magnesium Permeation in the Bacterial Divalent Cation Transport System CorA'''

==December 14, 2011: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations (slides)]]'''

==November 9, 2011: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snugtt2.pdf | How to deal with the new file system setup at SciNet (slides)]]'''

==October 12, 2011: SNUG TechTalk==
* Manuel Saldaña (Arch Es Computing) '''[[Media:ArchES-MPI-at-scinet2011.pdf | MPI as a programming model for High-Performance Reconfigurable Computers (slides)]]'''

==September 14, 2011: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:HPSS_rationale.pdf‎ | HPSS - SciNet's Storage Capacity Expansion (slides)]]'''

==June 8, 2011: SNUG TechTalk==
* Pierre de Buyl (CPTG Toronto/ULB Brussels) '''[http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html Fortran and Python (slides)]'''

==May 4, 2011: SNUG TechTalk==
* Peter Colberg (CPTG, Toronto) '''[[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind (slides)]]'''

==April 12, 2011: SNUG TechTalk==
* Rames van Zon (SciNet) '''[[Media:SNUGlocalsetup.pdf | User-Space Modules and Packages on SciNet (slides)]]'''

==March 9, 2011: SNUG TechTalks==
* Abdul Mroue (CITA, Toronto) '''[[Media:Mroue_SNUG_March_2011.pdf | Precessing Binary Black Hole Simulations (slides)]]'''
* Joachim Harnois-Déraps (CITA, Toronto) '''[[Media:Harnois_SNUG_March_2011.pdf | Weak Gravitational Lensing (slides)]]'''

==February 9, 2011: SNUG TechTalk==
* Seth Dworkin (Mechanical and Industrial Engineering, UoT) '''[[Media:SNUG_seminar_Feb_2011.pps | Computational Combustion: Toward the use of Sustainable and Alternative Fuels (slides)]]'''
* Ramses van Zon (SciNet) '''[[Media:Snugtrackjob.pdf | Job Monitoring on SciNet and Job Efficiency (slides)]]'''

==January 12, 2011: SNUG TechTalks==

* Sarah Rauscher (Regis Pomes group, Sick Kids, Toronto) '''[[Media:Rauscher_SNUG_Tech_Talk_Jan_12_2011.pdf | MD Simulations of Biomolecular Systems (slides)]]'''
* Bijia Pang (Ue-Li Pen group, CITA, UoT) '''[[Media:BPang_SNUG_Tech_Talk_Jan_12_2011.pdf | Black Hole Accretion on 17576 CPUs (slides)]]'''

==December 8, 2010: SNUG TechTalk==

* Jonathan Dursi (SciNet) '''[[Media:ProfillingTechTalk-Dec2010.pdf | Profiling and Tuning (slides)]]'''

==November 10, 2010: SNUG TechTalk ==

* Ramses van Zon (SciNet) '''[[Media:Snugdebug.pdf | Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb (slides)]]'''

==October 13, 2010: SNUG TechTalk==

* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_revcontrol.pdf|Version Control (slides)]]'''

==September 8, 2010: SNUG TechTalk==

* Ramses van Zon (SciNet) '''[[Media:Snugio.pdf | The Parallel File System and I/O (slides)]]'''

SciNet TechTalks and Seminars

2016-09-19T21:08:39Z

Mponce: /* Sept 14, 2016, SNUG TechTalk */

__NOTOC__
The SciNet Users Group (SNUG) meetings are every month on the second Wednesday, and involve pizza, user discussion, feedback, and a TechTalk or two (half-hour talk or two 15 minutes talks) on topics or technologies of interest to the SciNet community.

The pdfs of these TechTalks can be found here on the wiki. Below is a chronological list. Most pdfs can also be found on the [[Knowledge Base: Tutorials and Manuals |
Tutorials and manuals page]] which is ordered by topic.

== Sept 14, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet, UofT) 
Overview of 3D Scientific Visualization Tools: [[Media:Viz-tools_overview.pdf | slides]]

== Jun 8, 2016, SNUG TechTalk==
* Michael Wong (Codeplay/Canadian Head of Delegation to the C++ Standard) C++17: Will it be great or just OK?

== May 11, 2016, SNUG TechTalk==
* Jon Pipitone (CAMH) [https://support.scinet.utoronto.ca/education/get.php/qbatch.pdf qbatch - a tool for executing commands in parallel on clusters]

== Apr 13, 2016, SNUG TechTalk==
* AJ Guillon (Yetiware Inc.) Bewitched, Bothered and Bewildered: Parallelism and Memory Modules

== Feb 10, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ Scientific Visualization, an overview of VisIt]''' [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6400/ data]

== Dec 9, 2015, SNUG TechTalk ==
* Ramses van Zon (SciNet) [[Media:lmodtt.pdf|LMOD: a hierarchical system for software modules]]

== Nov 25, 2015: Seminar==
* Andre Recnik (University of Toronto) '''[[Media:missing.pdf|The CHIME X-Engine: A 7 PetaOP supercomputer with a 6.5 Tb/s network]]'''

== Oct 14, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:remoteviz.pdf|Remote graphics on the GPC: client-server application and VNC]]'''

== Sept 9, 2015: SNUG TechTalk==
* Leslie Barnes and Dylanne Dearborn (UoT) '''[[Media:ttdatamanagement.pdf|Research Data Management: A Brief Introduction]]'''

== Jun 10, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttrarray.pdf|Multidimensional Arrays in C++: rarrays]]'''

== Apr 8, 2015: SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/Snug/sph/mponce-sph_SNUG-apr2015.pdf Smoothed Particle Hydrodynamics: Applications to Astrophysical Simulations ]'''

== Mar 11, 2015: SNUG TechTalk==
* Mike Nolta (SciNet) '''[[Media:20150311-snug-newtools.pdf| Job and Queue Management ]]'''

== Feb 11, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttdata.pdf| Data Management and Transfer Tools at SciNet]]'''

== Nov 19, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]'''

== Oct 8, 2014: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''PyTables: Large Data and HDF5 in Python'''

== Sept 10, 2014: SNUG TechTalk==
* Jason Chong (SciNet) '''Globus'''

== May 14, 2014: SNUG TechTalk==
* Chris Szalwinski (Seneca College) '''[[Media:TechTalkSzalwinskiCilkPlus.pdf| Getting Started with Cilk Plus]]'''

== Apr 9, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snug_ish.pdf| Keep inventory of your data on different file systems with ISH]]'''

== Mar 12, 2014: SNUG TechTalk==
* Bertrand Brelier (IBM@SciNet) '''[[Media:NetCDF.pdf| Introduction to NetCDF4 binary files with Python, C++ and R]]'''

== Feb 12, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_XeonPhi.pdf| Introduction to the Xeon Phi]]'''

== Jan 15, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[IPython Notebook on GPC]]'''

== Dec 11, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttsystems.pdf|New and Existing Resources Available at SciNet]]'''

== Nov 13, 2013: SNUG TechTalk==
* Peter Colberg (SciNet) '''Self-propelled dimer motors: Small-code large-scale simulations using OpenCL and LuaJIT'''

== Oct 16, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Using MySQL on the GPC]]'''

== Sep 11, 2013: SNUG TechTalk==

* Peter Colberg (Chemistry, University of Toronto) '''[https://support.scinet.utoronto.ca/education/go.php/15/content.php/cid/18 Git-annex or: How I learned to stop worrying and manage the data]'''

== May 1, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:TechTalkJobMonitoring.pdf| Monitoring jobs at SciNet (slides)]]'''

== April 10, 2013: SNUG TechTalk==
* Scott Zuyderduyn (Bader Lab, U. of Toronto) '''Using GPUs to Model Higher-Dimensional Influences in Biological Networks'''

== Mar 13, 2013: SNUG TechTalk==
* Deepak Chandan (Phyics, University of Toronto) '''[[Media:TechTalkChandanSparseMKL.pdf| Using sparse matrices and solver routines from the Intel Math Kernel Library (slides)]]'''

== Feb 13, 2013: SNUG TechTalk==
* Ramses van Zon/Jaime Pinto (SciNet) '''[[Media:Hpss-TechTalkFeb2013.pdf|Demystifying HPSS (slides)]]'''

== Jan 9, 2013: SNUG TechTalk==
* Christopher Ing (Pomès Lab, Hospital for Sick Children, Toronto) '''[[Media:SNUG_Jan9.pdf|Interactive Computational Biology (slides)]]'''

==Dec 12, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Ttvnc.pdf|Faster remote graphical interfaces with VNC (slides)]]'''

==Nov 27, 2012: SciNet Bioinformatics Seminar==
* Sébastien Boisvert and Élénie Godzaridis (Laval) '''[[Media:BoisvertGodzaridis-presentation-for-biologists-and-bioinformaticians.pdf‎‎|Massively parallel assemblers for massively parallel DNA sequencers (slides)]]'''

==Nov 26, 2012: SciNet Developer Seminar==
*Élénie Godzaridis, Sébastien Boisvert (Laval) '''[[Media:GodzaridisBoisvert-presentation-for-computer-scientists.pdf|Granularities and messages: from design to abstraction to implementation to virtualization (slides)]]'''

==Nov 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (slides)]]'''

==Oct 24, 2012: SciNet Developer Seminar==
* Mark Ebersole (NVIDIA) '''[[Media:SciDevOpenACC.pdf|OpenACC (slides)]]'''

==Oct 23, 2012: SciNet Developer Seminar==
* Michael Nolta (CITA, Toronto) '''[[Media:Scinet_julia.pdf|The Julia Language (slides)]]'''

== Oct 10, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_BGQ.pdf|SciNet BlueGene/Q (slides)]]'''

== Oct 3, 2012: SciNet Developer Seminar==
* Kit Barton (IBM) '''[[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers (slides)]]'''

== Sep 12, 2012: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:SCIENCEDATA.pdf|Science is Data (slides)]]'''

==Jun 13, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Remotescinet.pdf | Remote development on SciNet (slides)]]'''

==May 9, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Adios-techtalk-may2012.pdf|ADIOS for Parallel IO (slides)]]''' [[Media:Adios-techtalk-may2012-src.tgz|source code]]

==Apr 11, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_Infiniband.pdf | SciNet's Infiniband Network & MPI options (slides)]]'''

==March 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:MKLTechTalkMarch2012.pdf | Intel Math Kernel Library (slides)]]'''

==February 8, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters (slides)]]'''

==January 11, 2012: SNUG TechTalk==
* Chris Neale, Pawel Pomorski, Nilmadhab Chakrabarti, Emil F. Pai, Régis Pomès (Sick Children's Hospital) '''Kinetics of Hydrophobic Gating and Energetics of Magnesium Permeation in the Bacterial Divalent Cation Transport System CorA'''

==December 14, 2011: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations (slides)]]'''

==November 9, 2011: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snugtt2.pdf | How to deal with the new file system setup at SciNet (slides)]]'''

==October 12, 2011: SNUG TechTalk==
* Manuel Saldaña (Arch Es Computing) '''[[Media:ArchES-MPI-at-scinet2011.pdf | MPI as a programming model for High-Performance Reconfigurable Computers (slides)]]'''

==September 14, 2011: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:HPSS_rationale.pdf‎ | HPSS - SciNet's Storage Capacity Expansion (slides)]]'''

==June 8, 2011: SNUG TechTalk==
* Pierre de Buyl (CPTG Toronto/ULB Brussels) '''[http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html Fortran and Python (slides)]'''

==May 4, 2011: SNUG TechTalk==
* Peter Colberg (CPTG, Toronto) '''[[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind (slides)]]'''

==April 12, 2011: SNUG TechTalk==
* Rames van Zon (SciNet) '''[[Media:SNUGlocalsetup.pdf | User-Space Modules and Packages on SciNet (slides)]]'''

==March 9, 2011: SNUG TechTalks==
* Abdul Mroue (CITA, Toronto) '''[[Media:Mroue_SNUG_March_2011.pdf | Precessing Binary Black Hole Simulations (slides)]]'''
* Joachim Harnois-Déraps (CITA, Toronto) '''[[Media:Harnois_SNUG_March_2011.pdf | Weak Gravitational Lensing (slides)]]'''

==February 9, 2011: SNUG TechTalk==
* Seth Dworkin (Mechanical and Industrial Engineering, UoT) '''[[Media:SNUG_seminar_Feb_2011.pps | Computational Combustion: Toward the use of Sustainable and Alternative Fuels (slides)]]'''
* Ramses van Zon (SciNet) '''[[Media:Snugtrackjob.pdf | Job Monitoring on SciNet and Job Efficiency (slides)]]'''

==January 12, 2011: SNUG TechTalks==

* Sarah Rauscher (Regis Pomes group, Sick Kids, Toronto) '''[[Media:Rauscher_SNUG_Tech_Talk_Jan_12_2011.pdf | MD Simulations of Biomolecular Systems (slides)]]'''
* Bijia Pang (Ue-Li Pen group, CITA, UoT) '''[[Media:BPang_SNUG_Tech_Talk_Jan_12_2011.pdf | Black Hole Accretion on 17576 CPUs (slides)]]'''

==December 8, 2010: SNUG TechTalk==

* Jonathan Dursi (SciNet) '''[[Media:ProfillingTechTalk-Dec2010.pdf | Profiling and Tuning (slides)]]'''

==November 10, 2010: SNUG TechTalk ==

* Ramses van Zon (SciNet) '''[[Media:Snugdebug.pdf | Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb (slides)]]'''

==October 13, 2010: SNUG TechTalk==

* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_revcontrol.pdf|Version Control (slides)]]'''

==September 8, 2010: SNUG TechTalk==

* Ramses van Zon (SciNet) '''[[Media:Snugio.pdf | The Parallel File System and I/O (slides)]]'''

SciNet TechTalks and Seminars

2016-09-19T21:07:50Z

Mponce: /* Sept 14, 2016, SNUG TechTalk */

__NOTOC__
The SciNet Users Group (SNUG) meetings are every month on the second Wednesday, and involve pizza, user discussion, feedback, and a TechTalk or two (half-hour talk or two 15 minutes talks) on topics or technologies of interest to the SciNet community.

The pdfs of these TechTalks can be found here on the wiki. Below is a chronological list. Most pdfs can also be found on the [[Knowledge Base: Tutorials and Manuals |
Tutorials and manuals page]] which is ordered by topic.

== Sept 14, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet, UofT) 
Overview of 3D Scientific Visualization Tools: [[Media:Viz-tools_overview.pdf]]

== Jun 8, 2016, SNUG TechTalk==
* Michael Wong (Codeplay/Canadian Head of Delegation to the C++ Standard) C++17: Will it be great or just OK?

== May 11, 2016, SNUG TechTalk==
* Jon Pipitone (CAMH) [https://support.scinet.utoronto.ca/education/get.php/qbatch.pdf qbatch - a tool for executing commands in parallel on clusters]

== Apr 13, 2016, SNUG TechTalk==
* AJ Guillon (Yetiware Inc.) Bewitched, Bothered and Bewildered: Parallelism and Memory Modules

== Feb 10, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ Scientific Visualization, an overview of VisIt]''' [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6400/ data]

== Dec 9, 2015, SNUG TechTalk ==
* Ramses van Zon (SciNet) [[Media:lmodtt.pdf|LMOD: a hierarchical system for software modules]]

== Nov 25, 2015: Seminar==
* Andre Recnik (University of Toronto) '''[[Media:missing.pdf|The CHIME X-Engine: A 7 PetaOP supercomputer with a 6.5 Tb/s network]]'''

== Oct 14, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:remoteviz.pdf|Remote graphics on the GPC: client-server application and VNC]]'''

== Sept 9, 2015: SNUG TechTalk==
* Leslie Barnes and Dylanne Dearborn (UoT) '''[[Media:ttdatamanagement.pdf|Research Data Management: A Brief Introduction]]'''

== Jun 10, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttrarray.pdf|Multidimensional Arrays in C++: rarrays]]'''

== Apr 8, 2015: SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/Snug/sph/mponce-sph_SNUG-apr2015.pdf Smoothed Particle Hydrodynamics: Applications to Astrophysical Simulations ]'''

== Mar 11, 2015: SNUG TechTalk==
* Mike Nolta (SciNet) '''[[Media:20150311-snug-newtools.pdf| Job and Queue Management ]]'''

== Feb 11, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttdata.pdf| Data Management and Transfer Tools at SciNet]]'''

== Nov 19, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]'''

== Oct 8, 2014: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''PyTables: Large Data and HDF5 in Python'''

== Sept 10, 2014: SNUG TechTalk==
* Jason Chong (SciNet) '''Globus'''

== May 14, 2014: SNUG TechTalk==
* Chris Szalwinski (Seneca College) '''[[Media:TechTalkSzalwinskiCilkPlus.pdf| Getting Started with Cilk Plus]]'''

== Apr 9, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snug_ish.pdf| Keep inventory of your data on different file systems with ISH]]'''

== Mar 12, 2014: SNUG TechTalk==
* Bertrand Brelier (IBM@SciNet) '''[[Media:NetCDF.pdf| Introduction to NetCDF4 binary files with Python, C++ and R]]'''

== Feb 12, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_XeonPhi.pdf| Introduction to the Xeon Phi]]'''

== Jan 15, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[IPython Notebook on GPC]]'''

== Dec 11, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttsystems.pdf|New and Existing Resources Available at SciNet]]'''

== Nov 13, 2013: SNUG TechTalk==
* Peter Colberg (SciNet) '''Self-propelled dimer motors: Small-code large-scale simulations using OpenCL and LuaJIT'''

== Oct 16, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Using MySQL on the GPC]]'''

== Sep 11, 2013: SNUG TechTalk==

* Peter Colberg (Chemistry, University of Toronto) '''[https://support.scinet.utoronto.ca/education/go.php/15/content.php/cid/18 Git-annex or: How I learned to stop worrying and manage the data]'''

== May 1, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:TechTalkJobMonitoring.pdf| Monitoring jobs at SciNet (slides)]]'''

== April 10, 2013: SNUG TechTalk==
* Scott Zuyderduyn (Bader Lab, U. of Toronto) '''Using GPUs to Model Higher-Dimensional Influences in Biological Networks'''

== Mar 13, 2013: SNUG TechTalk==
* Deepak Chandan (Phyics, University of Toronto) '''[[Media:TechTalkChandanSparseMKL.pdf| Using sparse matrices and solver routines from the Intel Math Kernel Library (slides)]]'''

== Feb 13, 2013: SNUG TechTalk==
* Ramses van Zon/Jaime Pinto (SciNet) '''[[Media:Hpss-TechTalkFeb2013.pdf|Demystifying HPSS (slides)]]'''

== Jan 9, 2013: SNUG TechTalk==
* Christopher Ing (Pomès Lab, Hospital for Sick Children, Toronto) '''[[Media:SNUG_Jan9.pdf|Interactive Computational Biology (slides)]]'''

==Dec 12, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Ttvnc.pdf|Faster remote graphical interfaces with VNC (slides)]]'''

==Nov 27, 2012: SciNet Bioinformatics Seminar==
* Sébastien Boisvert and Élénie Godzaridis (Laval) '''[[Media:BoisvertGodzaridis-presentation-for-biologists-and-bioinformaticians.pdf‎‎|Massively parallel assemblers for massively parallel DNA sequencers (slides)]]'''

==Nov 26, 2012: SciNet Developer Seminar==
*Élénie Godzaridis, Sébastien Boisvert (Laval) '''[[Media:GodzaridisBoisvert-presentation-for-computer-scientists.pdf|Granularities and messages: from design to abstraction to implementation to virtualization (slides)]]'''

==Nov 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (slides)]]'''

==Oct 24, 2012: SciNet Developer Seminar==
* Mark Ebersole (NVIDIA) '''[[Media:SciDevOpenACC.pdf|OpenACC (slides)]]'''

==Oct 23, 2012: SciNet Developer Seminar==
* Michael Nolta (CITA, Toronto) '''[[Media:Scinet_julia.pdf|The Julia Language (slides)]]'''

== Oct 10, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_BGQ.pdf|SciNet BlueGene/Q (slides)]]'''

== Oct 3, 2012: SciNet Developer Seminar==
* Kit Barton (IBM) '''[[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers (slides)]]'''

== Sep 12, 2012: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:SCIENCEDATA.pdf|Science is Data (slides)]]'''

==Jun 13, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Remotescinet.pdf | Remote development on SciNet (slides)]]'''

==May 9, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Adios-techtalk-may2012.pdf|ADIOS for Parallel IO (slides)]]''' [[Media:Adios-techtalk-may2012-src.tgz|source code]]

==Apr 11, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_Infiniband.pdf | SciNet's Infiniband Network & MPI options (slides)]]'''

==March 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:MKLTechTalkMarch2012.pdf | Intel Math Kernel Library (slides)]]'''

==February 8, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters (slides)]]'''

==January 11, 2012: SNUG TechTalk==
* Chris Neale, Pawel Pomorski, Nilmadhab Chakrabarti, Emil F. Pai, Régis Pomès (Sick Children's Hospital) '''Kinetics of Hydrophobic Gating and Energetics of Magnesium Permeation in the Bacterial Divalent Cation Transport System CorA'''

==December 14, 2011: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations (slides)]]'''

==November 9, 2011: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snugtt2.pdf | How to deal with the new file system setup at SciNet (slides)]]'''

==October 12, 2011: SNUG TechTalk==
* Manuel Saldaña (Arch Es Computing) '''[[Media:ArchES-MPI-at-scinet2011.pdf | MPI as a programming model for High-Performance Reconfigurable Computers (slides)]]'''

==September 14, 2011: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:HPSS_rationale.pdf‎ | HPSS - SciNet's Storage Capacity Expansion (slides)]]'''

==June 8, 2011: SNUG TechTalk==
* Pierre de Buyl (CPTG Toronto/ULB Brussels) '''[http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html Fortran and Python (slides)]'''

==May 4, 2011: SNUG TechTalk==
* Peter Colberg (CPTG, Toronto) '''[[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind (slides)]]'''

==April 12, 2011: SNUG TechTalk==
* Rames van Zon (SciNet) '''[[Media:SNUGlocalsetup.pdf | User-Space Modules and Packages on SciNet (slides)]]'''

==March 9, 2011: SNUG TechTalks==
* Abdul Mroue (CITA, Toronto) '''[[Media:Mroue_SNUG_March_2011.pdf | Precessing Binary Black Hole Simulations (slides)]]'''
* Joachim Harnois-Déraps (CITA, Toronto) '''[[Media:Harnois_SNUG_March_2011.pdf | Weak Gravitational Lensing (slides)]]'''

==February 9, 2011: SNUG TechTalk==
* Seth Dworkin (Mechanical and Industrial Engineering, UoT) '''[[Media:SNUG_seminar_Feb_2011.pps | Computational Combustion: Toward the use of Sustainable and Alternative Fuels (slides)]]'''
* Ramses van Zon (SciNet) '''[[Media:Snugtrackjob.pdf | Job Monitoring on SciNet and Job Efficiency (slides)]]'''

==January 12, 2011: SNUG TechTalks==

* Sarah Rauscher (Regis Pomes group, Sick Kids, Toronto) '''[[Media:Rauscher_SNUG_Tech_Talk_Jan_12_2011.pdf | MD Simulations of Biomolecular Systems (slides)]]'''
* Bijia Pang (Ue-Li Pen group, CITA, UoT) '''[[Media:BPang_SNUG_Tech_Talk_Jan_12_2011.pdf | Black Hole Accretion on 17576 CPUs (slides)]]'''

==December 8, 2010: SNUG TechTalk==

* Jonathan Dursi (SciNet) '''[[Media:ProfillingTechTalk-Dec2010.pdf | Profiling and Tuning (slides)]]'''

==November 10, 2010: SNUG TechTalk ==

* Ramses van Zon (SciNet) '''[[Media:Snugdebug.pdf | Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb (slides)]]'''

==October 13, 2010: SNUG TechTalk==

* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_revcontrol.pdf|Version Control (slides)]]'''

==September 8, 2010: SNUG TechTalk==

* Ramses van Zon (SciNet) '''[[Media:Snugio.pdf | The Parallel File System and I/O (slides)]]'''

SciNet TechTalks and Seminars

2016-09-14T18:23:33Z

Mponce:

__NOTOC__
The SciNet Users Group (SNUG) meetings are every month on the second Wednesday, and involve pizza, user discussion, feedback, and a TechTalk or two (half-hour talk or two 15 minutes talks) on topics or technologies of interest to the SciNet community.

The pdfs of these TechTalks can be found here on the wiki. Below is a chronological list. Most pdfs can also be found on the [[Knowledge Base: Tutorials and Manuals |
Tutorials and manuals page]] which is ordered by topic.

== Sept 14, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet, UofT) Overview of 3D Scientific Visualization Tools

== Jun 8, 2016, SNUG TechTalk==
* Michael Wong (Codeplay/Canadian Head of Delegation to the C++ Standard) C++17: Will it be great or just OK?

== May 11, 2016, SNUG TechTalk==
* Jon Pipitone (CAMH) [https://support.scinet.utoronto.ca/education/get.php/qbatch.pdf qbatch - a tool for executing commands in parallel on clusters]

== Apr 13, 2016, SNUG TechTalk==
* AJ Guillon (Yetiware Inc.) Bewitched, Bothered and Bewildered: Parallelism and Memory Modules

== Feb 10, 2016, SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ Scientific Visualization, an overview of VisIt]''' [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6400/ data]

== Dec 9, 2015, SNUG TechTalk ==
* Ramses van Zon (SciNet) [[Media:lmodtt.pdf|LMOD: a hierarchical system for software modules]]

== Nov 25, 2015: Seminar==
* Andre Recnik (University of Toronto) '''[[Media:missing.pdf|The CHIME X-Engine: A 7 PetaOP supercomputer with a 6.5 Tb/s network]]'''

== Oct 14, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:remoteviz.pdf|Remote graphics on the GPC: client-server application and VNC]]'''

== Sept 9, 2015: SNUG TechTalk==
* Leslie Barnes and Dylanne Dearborn (UoT) '''[[Media:ttdatamanagement.pdf|Research Data Management: A Brief Introduction]]'''

== Jun 10, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttrarray.pdf|Multidimensional Arrays in C++: rarrays]]'''

== Apr 8, 2015: SNUG TechTalk==
* Marcelo Ponce (SciNet) '''[https://support.scinet.utoronto.ca/Snug/sph/mponce-sph_SNUG-apr2015.pdf Smoothed Particle Hydrodynamics: Applications to Astrophysical Simulations ]'''

== Mar 11, 2015: SNUG TechTalk==
* Mike Nolta (SciNet) '''[[Media:20150311-snug-newtools.pdf| Job and Queue Management ]]'''

== Feb 11, 2015: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttdata.pdf| Data Management and Transfer Tools at SciNet]]'''

== Nov 19, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]'''

== Oct 8, 2014: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''PyTables: Large Data and HDF5 in Python'''

== Sept 10, 2014: SNUG TechTalk==
* Jason Chong (SciNet) '''Globus'''

== May 14, 2014: SNUG TechTalk==
* Chris Szalwinski (Seneca College) '''[[Media:TechTalkSzalwinskiCilkPlus.pdf| Getting Started with Cilk Plus]]'''

== Apr 9, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snug_ish.pdf| Keep inventory of your data on different file systems with ISH]]'''

== Mar 12, 2014: SNUG TechTalk==
* Bertrand Brelier (IBM@SciNet) '''[[Media:NetCDF.pdf| Introduction to NetCDF4 binary files with Python, C++ and R]]'''

== Feb 12, 2014: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_XeonPhi.pdf| Introduction to the Xeon Phi]]'''

== Jan 15, 2014: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[IPython Notebook on GPC]]'''

== Dec 11, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:ttsystems.pdf|New and Existing Resources Available at SciNet]]'''

== Nov 13, 2013: SNUG TechTalk==
* Peter Colberg (SciNet) '''Self-propelled dimer motors: Small-code large-scale simulations using OpenCL and LuaJIT'''

== Oct 16, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Using MySQL on the GPC]]'''

== Sep 11, 2013: SNUG TechTalk==

* Peter Colberg (Chemistry, University of Toronto) '''[https://support.scinet.utoronto.ca/education/go.php/15/content.php/cid/18 Git-annex or: How I learned to stop worrying and manage the data]'''

== May 1, 2013: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:TechTalkJobMonitoring.pdf| Monitoring jobs at SciNet (slides)]]'''

== April 10, 2013: SNUG TechTalk==
* Scott Zuyderduyn (Bader Lab, U. of Toronto) '''Using GPUs to Model Higher-Dimensional Influences in Biological Networks'''

== Mar 13, 2013: SNUG TechTalk==
* Deepak Chandan (Phyics, University of Toronto) '''[[Media:TechTalkChandanSparseMKL.pdf| Using sparse matrices and solver routines from the Intel Math Kernel Library (slides)]]'''

== Feb 13, 2013: SNUG TechTalk==
* Ramses van Zon/Jaime Pinto (SciNet) '''[[Media:Hpss-TechTalkFeb2013.pdf|Demystifying HPSS (slides)]]'''

== Jan 9, 2013: SNUG TechTalk==
* Christopher Ing (Pomès Lab, Hospital for Sick Children, Toronto) '''[[Media:SNUG_Jan9.pdf|Interactive Computational Biology (slides)]]'''

==Dec 12, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Ttvnc.pdf|Faster remote graphical interfaces with VNC (slides)]]'''

==Nov 27, 2012: SciNet Bioinformatics Seminar==
* Sébastien Boisvert and Élénie Godzaridis (Laval) '''[[Media:BoisvertGodzaridis-presentation-for-biologists-and-bioinformaticians.pdf‎‎|Massively parallel assemblers for massively parallel DNA sequencers (slides)]]'''

==Nov 26, 2012: SciNet Developer Seminar==
*Élénie Godzaridis, Sébastien Boisvert (Laval) '''[[Media:GodzaridisBoisvert-presentation-for-computer-scientists.pdf|Granularities and messages: from design to abstraction to implementation to virtualization (slides)]]'''

==Nov 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (slides)]]'''

==Oct 24, 2012: SciNet Developer Seminar==
* Mark Ebersole (NVIDIA) '''[[Media:SciDevOpenACC.pdf|OpenACC (slides)]]'''

==Oct 23, 2012: SciNet Developer Seminar==
* Michael Nolta (CITA, Toronto) '''[[Media:Scinet_julia.pdf|The Julia Language (slides)]]'''

== Oct 10, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_BGQ.pdf|SciNet BlueGene/Q (slides)]]'''

== Oct 3, 2012: SciNet Developer Seminar==
* Kit Barton (IBM) '''[[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers (slides)]]'''

== Sep 12, 2012: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:SCIENCEDATA.pdf|Science is Data (slides)]]'''

==Jun 13, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Remotescinet.pdf | Remote development on SciNet (slides)]]'''

==May 9, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Adios-techtalk-may2012.pdf|ADIOS for Parallel IO (slides)]]''' [[Media:Adios-techtalk-may2012-src.tgz|source code]]

==Apr 11, 2012: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_Infiniband.pdf | SciNet's Infiniband Network & MPI options (slides)]]'''

==March 14, 2012: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:MKLTechTalkMarch2012.pdf | Intel Math Kernel Library (slides)]]'''

==February 8, 2012: SNUG TechTalk==
* Jonathan Dursi (SciNet) '''[[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters (slides)]]'''

==January 11, 2012: SNUG TechTalk==
* Chris Neale, Pawel Pomorski, Nilmadhab Chakrabarti, Emil F. Pai, Régis Pomès (Sick Children's Hospital) '''Kinetics of Hydrophobic Gating and Energetics of Magnesium Permeation in the Bacterial Divalent Cation Transport System CorA'''

==December 14, 2011: SNUG TechTalk==
* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations (slides)]]'''

==November 9, 2011: SNUG TechTalk==
* Ramses van Zon (SciNet) '''[[Media:Snugtt2.pdf | How to deal with the new file system setup at SciNet (slides)]]'''

==October 12, 2011: SNUG TechTalk==
* Manuel Saldaña (Arch Es Computing) '''[[Media:ArchES-MPI-at-scinet2011.pdf | MPI as a programming model for High-Performance Reconfigurable Computers (slides)]]'''

==September 14, 2011: SNUG TechTalk==
* Jaime Pinto (SciNet) '''[[Media:HPSS_rationale.pdf‎ | HPSS - SciNet's Storage Capacity Expansion (slides)]]'''

==June 8, 2011: SNUG TechTalk==
* Pierre de Buyl (CPTG Toronto/ULB Brussels) '''[http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html Fortran and Python (slides)]'''

==May 4, 2011: SNUG TechTalk==
* Peter Colberg (CPTG, Toronto) '''[[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind (slides)]]'''

==April 12, 2011: SNUG TechTalk==
* Rames van Zon (SciNet) '''[[Media:SNUGlocalsetup.pdf | User-Space Modules and Packages on SciNet (slides)]]'''

==March 9, 2011: SNUG TechTalks==
* Abdul Mroue (CITA, Toronto) '''[[Media:Mroue_SNUG_March_2011.pdf | Precessing Binary Black Hole Simulations (slides)]]'''
* Joachim Harnois-Déraps (CITA, Toronto) '''[[Media:Harnois_SNUG_March_2011.pdf | Weak Gravitational Lensing (slides)]]'''

==February 9, 2011: SNUG TechTalk==
* Seth Dworkin (Mechanical and Industrial Engineering, UoT) '''[[Media:SNUG_seminar_Feb_2011.pps | Computational Combustion: Toward the use of Sustainable and Alternative Fuels (slides)]]'''
* Ramses van Zon (SciNet) '''[[Media:Snugtrackjob.pdf | Job Monitoring on SciNet and Job Efficiency (slides)]]'''

==January 12, 2011: SNUG TechTalks==

* Sarah Rauscher (Regis Pomes group, Sick Kids, Toronto) '''[[Media:Rauscher_SNUG_Tech_Talk_Jan_12_2011.pdf | MD Simulations of Biomolecular Systems (slides)]]'''
* Bijia Pang (Ue-Li Pen group, CITA, UoT) '''[[Media:BPang_SNUG_Tech_Talk_Jan_12_2011.pdf | Black Hole Accretion on 17576 CPUs (slides)]]'''

==December 8, 2010: SNUG TechTalk==

* Jonathan Dursi (SciNet) '''[[Media:ProfillingTechTalk-Dec2010.pdf | Profiling and Tuning (slides)]]'''

==November 10, 2010: SNUG TechTalk ==

* Ramses van Zon (SciNet) '''[[Media:Snugdebug.pdf | Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb (slides)]]'''

==October 13, 2010: SNUG TechTalk==

* Scott Northrup (SciNet) '''[[Media:Snug_techtalk_revcontrol.pdf|Version Control (slides)]]'''

==September 8, 2010: SNUG TechTalk==

* Ramses van Zon (SciNet) '''[[Media:Snugio.pdf | The Parallel File System and I/O (slides)]]'''

File:8 ComplexNetworks.pdf

2016-08-18T20:40:09Z

Mponce:

Knowledge Base: Tutorials and Manuals

2016-08-18T16:10:09Z

Mponce: /* Visualization */

__NOINDEX__
__TOC__
=Training material=

For upcoming classes, see our [https://support.scinet.utoronto.ca/education/ Training and Education website]!
==SciNet Basics==
* [[Media:SciNet_Tutorial.pdf|SciNet User Tutorial]]
* [[SciNet Command Line Utilities]]
* Intro to SciNet May 2014: [http://support.scinet.utoronto.ca/CourseVideo/SciNetIntroMay2014/IntroMay2014.html Video]/[[Media:IntroScinetMay2014.pdf|Slides]]
* SciNet Resources: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_SciNet_Resources/Monday_Morning_SciNet_Resources.mp4 Video]/ [[Media:Monday_Morning_SciNet_Resources.pdf|Slides]]
* [[Essentials]]
* [[FAQ|Frequenty asked questions]]
* [[Ssh]]
* [[GPC_Quickstart|GPC quickstart]]
* [[TCS_Quickstart|TCS quickstart]]
* [[GPU_Devel_Nodes|ARC/GPU quickstart]]
* [[Cell_Devel_Nodes|ARC/Cell quickstart]]
* [[Important .bashrc guidelines]]
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Software_and_Libraries | Software and libraries]]
* [[Installing your own modules]]
* [[Media:SNUGlocalsetup.pdf|User-space modules and packages (April 2011 SNUG TechTalk)]]
* [[Media:HPSS_rationale.pdf|HPSS - SciNet's storage capacity expansion]]
* BGQ Hardware Overview [https://support.scinet.utoronto.ca/~northrup/bgqhardware.pdf Slides ]/ [https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqhardware/bgqhardware.mp4 Video Recording ]
* Intro to Using the BGQ [[Media:Bgqintro.pdf|Slides ]]/[https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqintro/bgqintro.mp4 Video Recording ]

==Linux==
* [http://www.ee.surrey.ac.uk/Teaching/Unix/index.html Linux Tutorial] (warning: the last part of this tutorial is specific to the csh shell, whereas SciNet uses the bash shell).
* Linux Command Line: A Primer (June 2012) [[Media:SS_IntroToShell.pdf|Slides,]] [[Media:SS_IntroToShell.tgz|Files]]
* Introduction to the Linux Shell, SciNet, Mar 2012: [[Media:IntroToShell.pdf|Slides]] and [[Media:Shell-data.tgz|Data files]]

==Batch job management==
* [https://support.scinet.utoronto.ca/education/go.php/183/file_storage/index.php/download/1/files%5B%5D/3702/ Job and Queue Management Tools] (Techtalk Mar.11, 2015)
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (Techtalk Nov 14, 2012)]]
* [[Media:TechTalkJobMonitoring.pdf|Job Monitoring on SciNet and Job Efficiency]]

* [[Wallclock time]]
* [[Checkpoints]]
* [[Using_Signals|Signals]]
* [[Moab]]
* [[User_Serial|Serial Jobs (including GNU Parallel)]]
* [[User_Ramdisk|Ramdisk]]
* [http://www.clusterresources.com/products/mwm/docs/index.shtml Moab workload manager]
* [http://www.clusterresources.com/products/mwm/docs/a.gcommandoverview.shtml Moab commands]
* [http://www.clusterresources.com/products/torque/docs/ Torque resource manager]
* [http://www.clusterresources.com/products/torque/docs/a.acommands.shtml Torque PBS commands]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==Programming==
===General===
* [[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers]]: Slides fromt the SciNet Develop Seminar by Kit Barton, Sep 17, 2012.
* [[Media:Remotescinet.pdf‎|Remote Development]], slides from TechTalk Jun 13, 2012
* [[Scientific Software Development Course]], part I of the SciNet's Scientific Computing Course
* [http://software-carpentry.org Software Carpentry Resources]
* Version Control: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_BP_Revision_Control/Thursday_Morning_BP_Revision_Control.mp4 Video]/ [[Media:Snug_techtalk_revcontrol.pdf | Slides]]
* [[IBM_Nov_Workshop | IBM AIX Workshop, SciNet, Nov 2008 ]]
* [[IBM_Compiler_Workshop | IBM Compiler Workshop, SciNet, Feb 2009]]
* SNUG Techtalk Dec 2011 [[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations]]

===Fortran===
* Modern Fortran Course (1 day), SciNet, 19 Apr 2011
** [[Media:ModernFortran.pdf | Slides]]
** [[Media:ModernFortran.tgz | Source Code]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerp* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf IBM Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]

===C++===
* [[Media:Cpp11.pdf|Slides]] and [http://support.scinet.utoronto.ca/CourseVideo/Cpp11/cpp11.html recording] of the SciNet Developer Seminar on C++11, March 20, 2013
* Scientific C++ Course (1 day), SciNet, 15 March 2011
** [[Media:Scientific-c%2B%2B.pdf|Slides]] (updated on Apr 26, 2012)
** [[Media:Scinetcppexamples.tgz|Example source code]]
** [[Videos_of_the_One-Day_Scientific_C%2B%2B_Class | Videos of the Scientific C++ class]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerpro/en-us/cpp/lin/compiler_c/index.htm Intel C & C++ compiler]
ro/en-us/fortran/lin/compiler_f/index.htm Intel Fortran compiler]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf IBM C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]

===C===
* C refresher: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_C_Review/Monday_Morning_C_Review.mp4 Video]/ [[Media:Monday_Morning_C_Review.pdf| Slides]]
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf IBM C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]

===Cilk Plus===
* [[Media:TechTalkSzalwinskiCilkPlus.pdf|CilkPlus - Getting Started]] (slides of the May 2014 TechTalk by Chris Szalwinski)

===Hadoop===
* Introduction to Hadoop for HPCers, Part I - MapReduce: [[Media:Hadoop-PartI.pdf|Slides]], [[Media:HadoopPart1examples.tgz|Source Code]], [http://support.scinet.utoronto.ca/~ljdursi/SciNetHadoopVM.zip Virtual Machine]

===Perl===
* [[Perl]]
===Python===
* [[Python]]
* [[IPython Notebook on GPC]] (January 2014 TechTalk)
* [[Research Computing with Python]] (Modular Course, Fall 2013)
* [[Intro to Tkinter|Python GUIs with Python and TkInter]] [[Media:Tkinter.pdf|slides]] [[Media:Tkinter_code.tgz|code]]
* [http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html f2py: Fortran and Python] (June 2011 TechTalk by Pierre de Buyl)

===R===
* [[R Statistical Package]]
===Lua===
* [[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind]] (May 2011 TechTalk by Peter Colberg)

==Parallel Programming==
* [[2014 Ontario Summerschool on High Performance Computing Central]] (incl. OpenMP and MPI)
* [[High Performance Scientific Computing Course 2014]] (OpenMP and MPI, with video recordings of lectures)
* [[Media:SciNet_MPI3.0_seminar.pdf | MPI 3 Developer Seminar]]
* [[Media:Ds-openmp.pdf| OpenMP 4 Developer Seminar]]
* [[Ontario Summerschool on High Performance Computing Central]] (2013)
* [[High Performance Scientific Computing]], part 3 of SciNet's Scientific Computing Course (Winter 2012)
* Parallel Programming Course (5 days), SciNet, May 2011
** [[Parallel_Scientific_Computing_-_May_2011 | Videos, slides and code]]
* Parallel Computing for Computational Fluid Dynamics (CFD), SciNet, 23 March 2011
** [[Media:parCFD-mpi.pdf | Slides]]
** [[Media:parCFD.tgz | Source Code]]
* Intro to Practical Parallel Programming (1 day), SciNet, 22 Sept 2010:
**[[Media:PPP-Intro-Morning.pdf|Morning Slides, Intro and OpenMP ]]
**[[Media:PPP-Intro-Afternoon.pdf|Afternoon Slides, MPI]]
**[[Media:Intro-ppp.tgz|Example source code]]
* Parallel Scientific Computing Workshop (5 days), SciNet, Aug 2009:
**[[ Parallel_Scientific_Computing_-_Aug_09 | Slides ]]
**[http://www.cita.utoronto.ca/~ljdursi/PSP/ Video]
* [http://www.vscse.org/ Virtual School for CSE] Web courses (Jul/Aug 2010):
** Petascale programming environments and tools
** Big data for science
** Proven algorithmic techniques for many-core processors
* [https://computing.llnl.gov/tutorials/mpi/ LLNL MPI Tutorial]: This was the basis for the MPI workshop at SciNet.
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [[GPC MPI Versions]]
* [[Co-array Fortran on the GPC]]
* [[IBM_Feb_Workshop | IBM MPI Workshop, SciNet, Feb 2009]]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf IBM UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]

==GPU Computing==
* [[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]
* [[Media:Westgrid_CUDA.pdf | Intro to GPU Computing Using CUDA]] (WestGrid Spring 2014 Seminar Series)
* 1.5 hour intro to CUDA, March 2013: [[Media:CUDA-Graphics-Intro-2013.pdf | Slides]] and [[Media:CUDA-Graphics-Intro-2013.tgz | Source Code]]
* [[CUDA_Minicourse_Fall_2012 | CITA/SciNet CUDA Minicourse, Fall 2012]]
* [[SciNet GPU Workshop July 2010]]
* Intro to GPGPU Programming: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_GPGPU/Friday_Morning_GPGPU.mp4 Video]/ [[Media:Gpgpu.pdf | Slides]] (from 5 day parallel programming course at SciNet, May 2011)
* 1-day intro to GPGPU using CUDA Course (Aug 2011): [[Media:Intro-gpu.tgz | Source Code]], [[Media:IntroGPGPU-Aug2011.pdf | Slides]].
* [http://developer.nvidia.com/object/cuda_training.html NVidia archived courses for GPGPU Programming]
* [http://www.pgroup.com/doc/pgiug.pdf PGI Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf PGI Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf PGI Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf PGI CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf PGI OpenACC Getting Started Guide]

==Performance Tuning==
* [[Performance and Profiling Course, April 2013]]
* [[Introduction To Performance]]
* Performance tools for [[Performance_And_Debugging_Tools:_GPC | GPC ]] and [[Performance_And_Debugging_Tools:_TCS | TCS ]]
* Dec 2010 SNUG TechTalk: [[Media:ProfillingTechTalk-Dec2010.pdf | Profiling Tools on GPC]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters]] - SNUG TechTalk, Feb 2012
* [http://cnx.org/content/col11136/latest/ High Performance Computing Book] Online version of an older O'Reilly book which covers the basics of (mostly serial) programming for performance. Covers the most important issues today (such as cache) very clearly.
* [http://www.ece.cmu.edu/~franzf/papers/gttse07.pdf How to Write Fast Numerical Code ] Good introduction to thinking about performance and cache.

==Debugging==
* [[Parallel Debugging with DDT]]
* [[Media:SS_Debug.pdf|Debugging with GDB and DDT, half-day session at the Ontario HPC Summerschool 2012 Central Slides]], [[Media:SS_Debug.tgz|Code]].
* [[Media:Snugdebug.pdf|TechTalk: Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb], SciNet User Group Meeting, Nov 2010]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_Debugging/Thursday_Morning_Debugging.mp4 Video]
* [http://www.allinea.com/downloads/userguide.pdf Allinea DDT (Distributed Debugging Tool) User Guide]

==Math libraries (BLAS, LAPACK, FFT)==
* [[Media:MKLTechTalkMarch2012.pdf|Intel Math Kernel Library (MKL): An overview]] (TechTalk, March, 2012)
* [[Numerical Tools for Physical Scientists]], part 2 of SciNet's Scientific computing course, covers, random nubers, blas, lapack, fft, ...
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf Parallel ESSL high performance math library V3.3]
* [http://hal.inria.fr/inria-00576469 Linear Algebra Libraries] by Claire Mouton. 2009 INRIA Technical Report on existing linear algebra libraries for C++ (also here: [http://arxiv.org/abs/1103.3020])

==I/O==

* [[Media:NetCDF.pdf|Introduction to NetCDF4 binary files with Python, C++ and R (TechTalk March 2014)]]
* [[Using MySQL on the GPC]]
* [https://support.scinet.utoronto.ca/education/go.php/19/content.php/cid/59/ Relational Database Basics]
* [[Media:SCIENCEDATA.pdf‎|Sep 2012 SNUG TechTalk: Science=Data]]
* [[Data_Management|Data management]]
* Intro to Parallel I/O, SciNet, Oct 6th, 2010:
**[[Media:Parallel_io_course.pdf‎|Morning & MPI-IO Slides]]
**[[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
**[[Media:ParIO.tgz|Source Code]].
* Intro to Parallel I/O, SciNet, Feb, 2013
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-intro/pario-intro.mp4 Video of the Introduction]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-netcdfhdf5/pario-netcdfhdf5.mp4 Video of the parallel hdf5 and netcdf part] [[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-mpiio/pario-mpiio.mp4 Video of the MPI-IO part]
* Half-day HPCS2012 Parallel I/O tutorial, covering MPI-IO, HDF5, NetCDF, based on the above: [[Media:ParIO-HPCS2012.pdf|slides (pdf)]] and [[Media:ParIO-HPCS2012.tgz|source code]].
* [[Media:Snugio.pdf|Sept 2010 SNUG TechTalk: Parallel File System and IO]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_IO/Friday_Morning_IO.mp4 Video]
* [[File System and I/O dos and don'ts]]
* [[Media:40TB.pdf|So you have 40TB of Data]] -- an overview of things to consider with large data sets.
* [[Media:Adios-techtalk-may2012.pdf|May 2012 SNUG TechTalk: ADIOS for Parallel IO slides]] and [[Media:Adios-techtalk-may2012-src.tgz|source code]]
* [[hdf5_table|Writting / Reading a table in hdf5]]
* [[NetCDF_table|Writting / Reading a table in NetCDF]]
* Intro to Parallel I/O, SciNet, Sept 215
** MPI-IO [[Media:ParIO.MPIIO.2015.pdf |Slides]] and [[Media:ParIO.MPIIO.tar.gz | Sample codes]]
** [[Media:netcdf2015.pdf | NETCDF]] & [[Media:hfd5.pdf | HDF5]]

==Infiniband Networking==
* [[Media:Snug_techtalk_Infiniband.pdf | TechTalk on SciNet's Infiniband Network & MPI options ]]

==Visualization==
* [[Using Paraview]]
* [[VNC|VNC on the GPC]] (see also [[Media:Ttvnc.pdf|slides of the TechTalk on VNC]])
* [[Software_and_Libraries#anchor_viz|Visualization Software on the GPC]]
* [https://wiki.scinet.utoronto.ca/wiki/images/5/51/Remoteviz.pdf Remote visualization (X-forwarding and VNC)]
* [[Using Paraview]]
* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf gnuplot, xmgrace, remote visualization tools (X-forwarding and VNC), python's matplotlib]
* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Brief overview of ParaView & VisIt]
* [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ VisIt Basics]
* [https://support.scinet.utoronto.ca/education/go.php/273/file_storage/index.php/download/1/files%5B%5D/7363/ Scientific Visualization using VisIt (Basics and Advanced)], M.Ponce and A.Razoumov
* [https://support.scinet.utoronto.ca/education/get.php/8_ComplexNetworks.pdf Intro to Complex Networks Visualization, with Python]

* [http://scienceillustrated.ca Science Illustrated:] Two-day symposium on Visualizing Science, Feb 2011
* [http://www.kmdi.utoronto.ca/story/2011/03/si-science-illustrated-symposium-success Videos of the talks given at Science Illustrated] (recorded by [http://www.kmdi.utoronto.ca KMDI] at [http://www.utoronto.ca UoT]):
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=94ff5cd5-be6e-4fc6-9be6-dd2222342bcd Opening remarks] by Paul Young
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4255c34e-15e7-4b24-ba99-78f5c8fa4381 Information Visualization and the Myth of Information Overload] by Christopher Collins
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=adcf02bf-16cb-46cc-8cdc-1a65e9071d6b Beyond Basic Visualization] by Ramses Van Zon
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=47baf346-3599-4fa3-9b10-6a58faa6b33c Network Visualization & Analysis] by Igor Jurisica
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7e754a2e-7be5-476e-bb54-37def37bc07e Simulation and Visualization of Blood Flow] by David Steinman
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=d7622587-2c31-49c1-99d7-f0f16c078801 Scientific Visualizations: Does the Science Matter?] by Thomas Lucas
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=9963c637-6840-454f-a57f-9a1be6456616 How can visualization impact public perception of science?] Panelists: Jay Ingram, Peter Calamai, Reni Barlow, Hooley McLaughlin
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=88e50cff-db9b-4c71-b10d-781fec60a2c0 How Info Graphics are Created for the Mainstream Media] by Peter Calamai
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=3897e2a3-1fda-42be-ab78-edbab090fd9e Design Boot Camp] by Graham Huber
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4c27ed76-7292-407e-83a6-814e1461eccd Visualization Large Datasets] by Jonathan Dursi
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d49c845-3937-44e2-a300-9b8ffe57a857 Visualizing Colliding Black Holes] by Herald Pfeiffer
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d7e4803-39cd-4c8e-a443-bc2a7b1b3c28 Closing remarks] by Mubdi Rahman

==Applications==
{{:Knowledge Base: Applications}}
* See also [[User Codes]]

=Manuals=

==Intel compilers and libraries (GPC)==
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/cpp-lin/index.htm C & C++ compiler]
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/fortran-lin/index.htm Fortran compiler]
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [[Media:Compiler_qrg12.pdf‎|Intel Compiler Optimization Guide]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)

==IBM compilers and libraries (TCS/P7)==
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [[Media:essl51.pdf|ESSL high performance math library V5.1 for Linux on Power]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==PGI compilers (ARC)==
* [http://www.pgroup.com/doc/pgiug.pdf Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf OpenACC Getting Started Guide] (Note: $PGI/linux86-64/12.5/doc contains a newer version.)

==Scheduler (Adaptive Computing/Cluster Resources)==
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/help.htm Moab workload manager]
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/Content/a.gcommandoverview.html Moab commands]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm Torque resource manager]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm#topics/12-appendices/commandsOverview.htm Torque PBS commands]

==DDT Debugger (Allinea)==
* [http://www.allinea.com/downloads/userguide.pdf Distributed Debugging Tool User Guide]

Knowledge Base: Tutorials and Manuals

2016-08-18T15:58:51Z

Mponce: /* Visualization */

__NOINDEX__
__TOC__
=Training material=

For upcoming classes, see our [https://support.scinet.utoronto.ca/education/ Training and Education website]!
==SciNet Basics==
* [[Media:SciNet_Tutorial.pdf|SciNet User Tutorial]]
* [[SciNet Command Line Utilities]]
* Intro to SciNet May 2014: [http://support.scinet.utoronto.ca/CourseVideo/SciNetIntroMay2014/IntroMay2014.html Video]/[[Media:IntroScinetMay2014.pdf|Slides]]
* SciNet Resources: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_SciNet_Resources/Monday_Morning_SciNet_Resources.mp4 Video]/ [[Media:Monday_Morning_SciNet_Resources.pdf|Slides]]
* [[Essentials]]
* [[FAQ|Frequenty asked questions]]
* [[Ssh]]
* [[GPC_Quickstart|GPC quickstart]]
* [[TCS_Quickstart|TCS quickstart]]
* [[GPU_Devel_Nodes|ARC/GPU quickstart]]
* [[Cell_Devel_Nodes|ARC/Cell quickstart]]
* [[Important .bashrc guidelines]]
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Software_and_Libraries | Software and libraries]]
* [[Installing your own modules]]
* [[Media:SNUGlocalsetup.pdf|User-space modules and packages (April 2011 SNUG TechTalk)]]
* [[Media:HPSS_rationale.pdf|HPSS - SciNet's storage capacity expansion]]
* BGQ Hardware Overview [https://support.scinet.utoronto.ca/~northrup/bgqhardware.pdf Slides ]/ [https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqhardware/bgqhardware.mp4 Video Recording ]
* Intro to Using the BGQ [[Media:Bgqintro.pdf|Slides ]]/[https://support.scinet.utoronto.ca/CourseVideo/BGQ/bgqintro/bgqintro.mp4 Video Recording ]

==Linux==
* [http://www.ee.surrey.ac.uk/Teaching/Unix/index.html Linux Tutorial] (warning: the last part of this tutorial is specific to the csh shell, whereas SciNet uses the bash shell).
* Linux Command Line: A Primer (June 2012) [[Media:SS_IntroToShell.pdf|Slides,]] [[Media:SS_IntroToShell.tgz|Files]]
* Introduction to the Linux Shell, SciNet, Mar 2012: [[Media:IntroToShell.pdf|Slides]] and [[Media:Shell-data.tgz|Data files]]

==Batch job management==
* [https://support.scinet.utoronto.ca/education/go.php/183/file_storage/index.php/download/1/files%5B%5D/3702/ Job and Queue Management Tools] (Techtalk Mar.11, 2015)
* [[Media:LargeScaleBio.pdf‎|Workflow Optimization (w/focus on Large Scale BioInformatics)]]
* [[Media:Tech-talk-gnu-parallel.pdf|GNU Parallel (Techtalk Nov 14, 2012)]]
* [[Media:TechTalkJobMonitoring.pdf|Job Monitoring on SciNet and Job Efficiency]]

* [[Wallclock time]]
* [[Checkpoints]]
* [[Using_Signals|Signals]]
* [[Moab]]
* [[User_Serial|Serial Jobs (including GNU Parallel)]]
* [[User_Ramdisk|Ramdisk]]
* [http://www.clusterresources.com/products/mwm/docs/index.shtml Moab workload manager]
* [http://www.clusterresources.com/products/mwm/docs/a.gcommandoverview.shtml Moab commands]
* [http://www.clusterresources.com/products/torque/docs/ Torque resource manager]
* [http://www.clusterresources.com/products/torque/docs/a.acommands.shtml Torque PBS commands]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==Programming==
===General===
* [[Media:SciDev-XLCompilers.pdf|Performance Tuning with the IBM XL Compilers]]: Slides fromt the SciNet Develop Seminar by Kit Barton, Sep 17, 2012.
* [[Media:Remotescinet.pdf‎|Remote Development]], slides from TechTalk Jun 13, 2012
* [[Scientific Software Development Course]], part I of the SciNet's Scientific Computing Course
* [http://software-carpentry.org Software Carpentry Resources]
* Version Control: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_BP_Revision_Control/Thursday_Morning_BP_Revision_Control.mp4 Video]/ [[Media:Snug_techtalk_revcontrol.pdf | Slides]]
* [[IBM_Nov_Workshop | IBM AIX Workshop, SciNet, Nov 2008 ]]
* [[IBM_Compiler_Workshop | IBM Compiler Workshop, SciNet, Feb 2009]]
* SNUG Techtalk Dec 2011 [[Media:Snug_techtalk_compiler.pdf | Intel Compiler Optimizations]]

===Fortran===
* Modern Fortran Course (1 day), SciNet, 19 Apr 2011
** [[Media:ModernFortran.pdf | Slides]]
** [[Media:ModernFortran.tgz | Source Code]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerp* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf IBM Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]

===C++===
* [[Media:Cpp11.pdf|Slides]] and [http://support.scinet.utoronto.ca/CourseVideo/Cpp11/cpp11.html recording] of the SciNet Developer Seminar on C++11, March 20, 2013
* Scientific C++ Course (1 day), SciNet, 15 March 2011
** [[Media:Scientific-c%2B%2B.pdf|Slides]] (updated on Apr 26, 2012)
** [[Media:Scinetcppexamples.tgz|Example source code]]
** [[Videos_of_the_One-Day_Scientific_C%2B%2B_Class | Videos of the Scientific C++ class]]
* [http://software.intel.com/sites/products/documentation/hpc/compilerpro/en-us/cpp/lin/compiler_c/index.htm Intel C & C++ compiler]
ro/en-us/fortran/lin/compiler_f/index.htm Intel Fortran compiler]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf IBM C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]

===C===
* C refresher: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Monday_Morning_C_Review/Monday_Morning_C_Review.mp4 Video]/ [[Media:Monday_Morning_C_Review.pdf| Slides]]
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf IBM C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]

===Cilk Plus===
* [[Media:TechTalkSzalwinskiCilkPlus.pdf|CilkPlus - Getting Started]] (slides of the May 2014 TechTalk by Chris Szalwinski)

===Hadoop===
* Introduction to Hadoop for HPCers, Part I - MapReduce: [[Media:Hadoop-PartI.pdf|Slides]], [[Media:HadoopPart1examples.tgz|Source Code]], [http://support.scinet.utoronto.ca/~ljdursi/SciNetHadoopVM.zip Virtual Machine]

===Perl===
* [[Perl]]
===Python===
* [[Python]]
* [[IPython Notebook on GPC]] (January 2014 TechTalk)
* [[Research Computing with Python]] (Modular Course, Fall 2013)
* [[Intro to Tkinter|Python GUIs with Python and TkInter]] [[Media:Tkinter.pdf|slides]] [[Media:Tkinter_code.tgz|code]]
* [http://support.scinet.utoronto.ca/Snug/scinet-f2py/scinet-f2py.html f2py: Fortran and Python] (June 2011 TechTalk by Pierre de Buyl)

===R===
* [[R Statistical Package]]
===Lua===
* [[Media:PeterColberg_Lua_scinet.pdf | Scripting HALMD with Lua and Luabind]] (May 2011 TechTalk by Peter Colberg)

==Parallel Programming==
* [[2014 Ontario Summerschool on High Performance Computing Central]] (incl. OpenMP and MPI)
* [[High Performance Scientific Computing Course 2014]] (OpenMP and MPI, with video recordings of lectures)
* [[Media:SciNet_MPI3.0_seminar.pdf | MPI 3 Developer Seminar]]
* [[Media:Ds-openmp.pdf| OpenMP 4 Developer Seminar]]
* [[Ontario Summerschool on High Performance Computing Central]] (2013)
* [[High Performance Scientific Computing]], part 3 of SciNet's Scientific Computing Course (Winter 2012)
* Parallel Programming Course (5 days), SciNet, May 2011
** [[Parallel_Scientific_Computing_-_May_2011 | Videos, slides and code]]
* Parallel Computing for Computational Fluid Dynamics (CFD), SciNet, 23 March 2011
** [[Media:parCFD-mpi.pdf | Slides]]
** [[Media:parCFD.tgz | Source Code]]
* Intro to Practical Parallel Programming (1 day), SciNet, 22 Sept 2010:
**[[Media:PPP-Intro-Morning.pdf|Morning Slides, Intro and OpenMP ]]
**[[Media:PPP-Intro-Afternoon.pdf|Afternoon Slides, MPI]]
**[[Media:Intro-ppp.tgz|Example source code]]
* Parallel Scientific Computing Workshop (5 days), SciNet, Aug 2009:
**[[ Parallel_Scientific_Computing_-_Aug_09 | Slides ]]
**[http://www.cita.utoronto.ca/~ljdursi/PSP/ Video]
* [http://www.vscse.org/ Virtual School for CSE] Web courses (Jul/Aug 2010):
** Petascale programming environments and tools
** Big data for science
** Proven algorithmic techniques for many-core processors
* [https://computing.llnl.gov/tutorials/mpi/ LLNL MPI Tutorial]: This was the basis for the MPI workshop at SciNet.
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [[GPC MPI Versions]]
* [[Co-array Fortran on the GPC]]
* [[IBM_Feb_Workshop | IBM MPI Workshop, SciNet, Feb 2009]]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf IBM UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]

==GPU Computing==
* [[Media:SNUG_NOV_CUDA.pdf | New Features in CUDA 5 & 6, Nov. 2014]]
* [[Media:Westgrid_CUDA.pdf | Intro to GPU Computing Using CUDA]] (WestGrid Spring 2014 Seminar Series)
* 1.5 hour intro to CUDA, March 2013: [[Media:CUDA-Graphics-Intro-2013.pdf | Slides]] and [[Media:CUDA-Graphics-Intro-2013.tgz | Source Code]]
* [[CUDA_Minicourse_Fall_2012 | CITA/SciNet CUDA Minicourse, Fall 2012]]
* [[SciNet GPU Workshop July 2010]]
* Intro to GPGPU Programming: [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_GPGPU/Friday_Morning_GPGPU.mp4 Video]/ [[Media:Gpgpu.pdf | Slides]] (from 5 day parallel programming course at SciNet, May 2011)
* 1-day intro to GPGPU using CUDA Course (Aug 2011): [[Media:Intro-gpu.tgz | Source Code]], [[Media:IntroGPGPU-Aug2011.pdf | Slides]].
* [http://developer.nvidia.com/object/cuda_training.html NVidia archived courses for GPGPU Programming]
* [http://www.pgroup.com/doc/pgiug.pdf PGI Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf PGI Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf PGI Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf PGI CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf PGI OpenACC Getting Started Guide]

==Performance Tuning==
* [[Performance and Profiling Course, April 2013]]
* [[Introduction To Performance]]
* Performance tools for [[Performance_And_Debugging_Tools:_GPC | GPC ]] and [[Performance_And_Debugging_Tools:_TCS | TCS ]]
* Dec 2010 SNUG TechTalk: [[Media:ProfillingTechTalk-Dec2010.pdf | Profiling Tools on GPC]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [[Media:Mpi-tuning-parameters.pdf‎ | MPI Tuning Parameters]] - SNUG TechTalk, Feb 2012
* [http://cnx.org/content/col11136/latest/ High Performance Computing Book] Online version of an older O'Reilly book which covers the basics of (mostly serial) programming for performance. Covers the most important issues today (such as cache) very clearly.
* [http://www.ece.cmu.edu/~franzf/papers/gttse07.pdf How to Write Fast Numerical Code ] Good introduction to thinking about performance and cache.

==Debugging==
* [[Parallel Debugging with DDT]]
* [[Media:SS_Debug.pdf|Debugging with GDB and DDT, half-day session at the Ontario HPC Summerschool 2012 Central Slides]], [[Media:SS_Debug.tgz|Code]].
* [[Media:Snugdebug.pdf|TechTalk: Debuggers & Parallel Debugging on SciNet - gdb, ddd, padb], SciNet User Group Meeting, Nov 2010]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Thursday_Morning_Debugging/Thursday_Morning_Debugging.mp4 Video]
* [http://www.allinea.com/downloads/userguide.pdf Allinea DDT (Distributed Debugging Tool) User Guide]

==Math libraries (BLAS, LAPACK, FFT)==
* [[Media:MKLTechTalkMarch2012.pdf|Intel Math Kernel Library (MKL): An overview]] (TechTalk, March, 2012)
* [[Numerical Tools for Physical Scientists]], part 2 of SciNet's Scientific computing course, covers, random nubers, blas, lapack, fft, ...
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf Parallel ESSL high performance math library V3.3]
* [http://hal.inria.fr/inria-00576469 Linear Algebra Libraries] by Claire Mouton. 2009 INRIA Technical Report on existing linear algebra libraries for C++ (also here: [http://arxiv.org/abs/1103.3020])

==I/O==

* [[Media:NetCDF.pdf|Introduction to NetCDF4 binary files with Python, C++ and R (TechTalk March 2014)]]
* [[Using MySQL on the GPC]]
* [https://support.scinet.utoronto.ca/education/go.php/19/content.php/cid/59/ Relational Database Basics]
* [[Media:SCIENCEDATA.pdf‎|Sep 2012 SNUG TechTalk: Science=Data]]
* [[Data_Management|Data management]]
* Intro to Parallel I/O, SciNet, Oct 6th, 2010:
**[[Media:Parallel_io_course.pdf‎|Morning & MPI-IO Slides]]
**[[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
**[[Media:ParIO.tgz|Source Code]].
* Intro to Parallel I/O, SciNet, Feb, 2013
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-intro/pario-intro.mp4 Video of the Introduction]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-netcdfhdf5/pario-netcdfhdf5.mp4 Video of the parallel hdf5 and netcdf part] [[Media:Netcdfhdf5.pdf|NetCDF/HDF5 Slides]]
** [http://support.scinet.utoronto.ca/CourseVideo/ParallelIOcourse/pario-mpiio/pario-mpiio.mp4 Video of the MPI-IO part]
* Half-day HPCS2012 Parallel I/O tutorial, covering MPI-IO, HDF5, NetCDF, based on the above: [[Media:ParIO-HPCS2012.pdf|slides (pdf)]] and [[Media:ParIO-HPCS2012.tgz|source code]].
* [[Media:Snugio.pdf|Sept 2010 SNUG TechTalk: Parallel File System and IO]] [http://support.scinet.utoronto.ca/CourseVideo/PPPcourse/Friday_Morning_IO/Friday_Morning_IO.mp4 Video]
* [[File System and I/O dos and don'ts]]
* [[Media:40TB.pdf|So you have 40TB of Data]] -- an overview of things to consider with large data sets.
* [[Media:Adios-techtalk-may2012.pdf|May 2012 SNUG TechTalk: ADIOS for Parallel IO slides]] and [[Media:Adios-techtalk-may2012-src.tgz|source code]]
* [[hdf5_table|Writting / Reading a table in hdf5]]
* [[NetCDF_table|Writting / Reading a table in NetCDF]]
* Intro to Parallel I/O, SciNet, Sept 215
** MPI-IO [[Media:ParIO.MPIIO.2015.pdf |Slides]] and [[Media:ParIO.MPIIO.tar.gz | Sample codes]]
** [[Media:netcdf2015.pdf | NETCDF]] & [[Media:hfd5.pdf | HDF5]]

==Infiniband Networking==
* [[Media:Snug_techtalk_Infiniband.pdf | TechTalk on SciNet's Infiniband Network & MPI options ]]

==Visualization==
* [[Using Paraview]]
* [[VNC|VNC on the GPC]] (see also [[Media:Ttvnc.pdf|slides of the TechTalk on VNC]])
* [[Software_and_Libraries#anchor_viz|Visualization Software on the GPC]]
* [https://wiki.scinet.utoronto.ca/wiki/images/5/51/Remoteviz.pdf Remote visualization (X-forwarding and VNC)]

* [https://support.scinet.utoronto.ca/~mponce/Ottawa/ss2016_visualization-I.pdf gnuplot, xmgrace, remote visualization tools (X-forwarding and VNC), python's matplotlib]
* [https://support.scinet.utoronto.ca/~mponce/Ottawa/ss2016_visualization-II.pdf Brief overview of ParaView & VisIt]
* [https://support.scinet.utoronto.ca/education/go.php/242/file_storage/index.php/download/1/files%5B%5D/6399/ VisIt Basics]
* [https://support.scinet.utoronto.ca/education/get.php/8_ComplexNetworks.pdf Intro to Complex Networks Visualization, with Python]

* [http://scienceillustrated.ca Science Illustrated:] Two-day symposium on Visualizing Science, Feb 2011
* [http://www.kmdi.utoronto.ca/story/2011/03/si-science-illustrated-symposium-success Videos of the talks given at Science Illustrated] (recorded by [http://www.kmdi.utoronto.ca KMDI] at [http://www.utoronto.ca UoT]):
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=94ff5cd5-be6e-4fc6-9be6-dd2222342bcd Opening remarks] by Paul Young
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4255c34e-15e7-4b24-ba99-78f5c8fa4381 Information Visualization and the Myth of Information Overload] by Christopher Collins
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=adcf02bf-16cb-46cc-8cdc-1a65e9071d6b Beyond Basic Visualization] by Ramses Van Zon
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=47baf346-3599-4fa3-9b10-6a58faa6b33c Network Visualization & Analysis] by Igor Jurisica
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7e754a2e-7be5-476e-bb54-37def37bc07e Simulation and Visualization of Blood Flow] by David Steinman
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=d7622587-2c31-49c1-99d7-f0f16c078801 Scientific Visualizations: Does the Science Matter?] by Thomas Lucas
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=9963c637-6840-454f-a57f-9a1be6456616 How can visualization impact public perception of science?] Panelists: Jay Ingram, Peter Calamai, Reni Barlow, Hooley McLaughlin
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=88e50cff-db9b-4c71-b10d-781fec60a2c0 How Info Graphics are Created for the Mainstream Media] by Peter Calamai
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=3897e2a3-1fda-42be-ab78-edbab090fd9e Design Boot Camp] by Graham Huber
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=4c27ed76-7292-407e-83a6-814e1461eccd Visualization Large Datasets] by Jonathan Dursi
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d49c845-3937-44e2-a300-9b8ffe57a857 Visualizing Colliding Black Holes] by Herald Pfeiffer
** [http://itube.ischool.utoronto.ca/Panopto/Pages/Viewer/Default.aspx?id=7d7e4803-39cd-4c8e-a443-bc2a7b1b3c28 Closing remarks] by Mubdi Rahman

==Applications==
{{:Knowledge Base: Applications}}
* See also [[User Codes]]

=Manuals=

==Intel compilers and libraries (GPC)==
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/cpp-lin/index.htm C & C++ compiler]
* [http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/fortran-lin/index.htm Fortran compiler]
* [[Media:FP_Consistency.pdf|Intel Compiler Floating Point Consistency]]
* [[Media:Compiler_qrg12.pdf‎|Intel Compiler Optimization Guide]]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/lin/index.htm Math Kernel Library (MKL)]
* [http://software.intel.com/sites/products/documentation/hpc/mkl/vsl/vslnotes.pdf Math Kernel Library's Vector Statistical Library]
* [http://software.intel.com/sites/products/documentation/hpc/mpi/linux/reference_manual.pdf Intel MPI library]
* [http://software.intel.com/en-us/articles/intel-mkl-link-line-advisor Math Kernel Library link line advisor] ($MKLPATH → ${MKLPATH} in makefiles)

==IBM compilers and libraries (TCS/P7)==
* [http://support.scinet.utoronto.ca/Manuals/xlc-compiler.pdf C compiler], [http://support.scinet.utoronto.ca/Manuals/xlc-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlc-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlC++-compiler.pdf C++ compiler], [http://support.scinet.utoronto.ca/Manuals/xlC++-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlC++-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/xlf-compiler.pdf Fortran compiler] [http://support.scinet.utoronto.ca/Manuals/xlf-langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/xlf-proguide.pdf optimization]
* [http://support.scinet.utoronto.ca/Manuals/UPC/compiler.pdf UPC compiler], [http://support.scinet.utoronto.ca/Manuals/UPC/langref.pdf language], [http://support.scinet.utoronto.ca/Manuals/UPC/upcopt.pdf optimization], [http://support.scinet.utoronto.ca/Manuals/UPC/standlib.pdf library], [http://support.scinet.utoronto.ca/Manuals/UPC/upcusersguide.pdf user's guide], [http://support.scinet.utoronto.ca/Manuals/UPC/proguide.pdf programmer's guide]
* [http://publib.boulder.ibm.com/epubs/pdf/am501405.pdf ESSL high performance math library V4] ([http://publib.boulder.ibm.com/epubs/pdf/am601305.pdf V3])
* [[Media:essl51.pdf|ESSL high performance math library V5.1 for Linux on Power]]
* [http://support.scinet.utoronto.ca/Manuals/JUMP-AIX-POWER6-AppsPerformanceTuning-wp032008.pdf Performance tuning]
* [http://support.scinet.utoronto.ca/Manuals/PE5.1-operationanduse.pdf Parallel environment]
* [http://publib.boulder.ibm.com/infocenter/clresctr/vxrx/index.jsp Cluster information center] (with error codes)
* [http://support.scinet.utoronto.ca/Manuals/LL-usingandadministering.pdf LoadLeveler: using & administering]

==PGI compilers (ARC)==
* [http://www.pgroup.com/doc/pgiug.pdf Compiler User's Guide]
* [http://www.pgroup.com/doc/pgiref.pdf Compiler Reference Manual]
* [http://www.pgroup.com/doc/pgifortref.pdf Fortran reference]
* [http://www.pgroup.com/doc/pgicudaforug.pdf CUDA Fortran Programming Guide and Reference]
* [http://www.pgroup.com/doc/openACC_gs.pdf OpenACC Getting Started Guide] (Note: $PGI/linux86-64/12.5/doc contains a newer version.)

==Scheduler (Adaptive Computing/Cluster Resources)==
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/help.htm Moab workload manager]
* [http://docs.adaptivecomputing.com/mwm/archive/7-0/Content/a.gcommandoverview.html Moab commands]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm Torque resource manager]
* [http://docs.adaptivecomputing.com/torque/archive/4-0-1/help.htm#topics/12-appendices/commandsOverview.htm Torque PBS commands]

==DDT Debugger (Allinea)==
* [http://www.allinea.com/downloads/userguide.pdf Distributed Debugging Tool User Guide]

2016 Ontario Summer School for High Performance Computing Central

2016-07-15T12:02:48Z

Mponce: /* Slides */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
* Morning datasets and scripts: [[Media:Data_scripts.tar.gz | datsets and scripts]]

* Python scripts: [[Media:Codes_examples.tar.gz‎ | python's scripts]]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====
* [[Media:debug.pdf | Slides]]

* [[Media:Debugcode.tar.gz | Examples]]

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-15T12:02:06Z

Mponce: /* Slides and other material */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
* Morning datasets and scripts: [[Media:Data_scripts.tar.gz | datsets and scripts]]

* Python scripts: [[Media:Codes_examples.tar.gz‎ | python's scripts]]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====
* [[Media:debug.pdf | Slides]]

* [[Media:Debugcode.tar.gz | Examples]]

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-15T12:01:45Z

Mponce: /* Datasets & Scripts */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
* Morning datasets and scripts: [[Media:Data_scripts.tar.gz | datsets and scripts]]

* Python scripts: [[Media:Codes_examples.tar.gz‎ | python's scripts]]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

* [https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====
Slides: [[Media:debug.pdf]]

Examples: [[Media:Debugcode.tar.gz]]

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-15T12:01:23Z

Mponce: /* Datasets & Scripts */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
* Morning datasets and scripts: [[Media:Data_scripts.tar.gz | datsets and scripts]]

* Python scripts: [[Media:Codes_examples.tar.gz‎ | python's scripts]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====
Slides: [[Media:debug.pdf]]

Examples: [[Media:Debugcode.tar.gz]]

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-15T11:59:31Z

Mponce: /* Slides and other material */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

Python scripts: [[Media:Codes_examples.tar.gz‎]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====
Slides: [[Media:debug.pdf]]

Examples: [[Media:Debugcode.tar.gz]]

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

File:Debug.pdf

2016-07-15T11:57:11Z

Mponce:

2016 Ontario Summer School for High Performance Computing Central

2016-07-14T17:17:41Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets & Scripts======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

Python scripts: [[Media:Codes_examples.tar.gz‎]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-14T17:16:02Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

Python scripts: [[Media:Codes_examples.tar.gz‎]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

File:Codes examples.tar.gz

2016-07-14T17:14:40Z

Mponce:

2016 Ontario Summer School for High Performance Computing Central

2016-07-14T17:07:08Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Memorial Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

===Group Picture===

[[File:grouppic_small.jpg|640px]]

Taken Wednesday July 13, 2016.

__TOC__

===Sessions===

====Introduction to HPC and SciNet====

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

====Programming Shared Memory Systems with OpenMP====

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

====Introduction to the Linux Shell====

=====Abstract=====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

=====Details=====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
A laptop with a linux-like environment.

=====Slides and other material=====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

====R for Data Science====

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

====Programming Clusters with MPI====

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

====Parallel R for Data Science====

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

====Python for Scientific Computing====

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

====Python for High Performance Computing====

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, mpi4py and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [[Media:hpcpy.pdf | Parallel Python Slides]]
* [[Media:hpcpycode.tar.gz | Parallel Python Code]]

----

====Programming GPUs with CUDA====

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

[http://ppomorsk.sharcnet.ca/CUDA_day1_2016.tar.gz slides and code for day 1]

----

====Visualization====

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

Python scripts: [[Media:codes_examples.zip]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

====Debugging====

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

====Bring Your Own Code====

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-13T14:19:02Z

Mponce: /* Details */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-13T13:54:34Z

Mponce: /* Prerequisites */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows machines, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphics capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-13T13:53:48Z

Mponce: /* Prerequisites */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/1/1a/Intro_Python.pdf Slides]
----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

For windows user, it will be useful to install a
[https://wiki.scinet.utoronto.ca/wiki/index.php/FAQ#Do_you_have_a_recommended_ssh_program_that_will_allow_scinet_access_from_Windows_machines.3F ssh-client]
with graphic capabilities.

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-12T19:50:41Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
Morning datasets and scripts: [[Media:Data_scripts.tar.gz]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-12T19:50:21Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
[[Media:Data_scripts.tar.gz Morning datasets and scripts]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-12T19:50:04Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
[[Media:Data_scripts.tar.gz]]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

File:Data scripts.tar.gz

2016-07-12T19:48:49Z

Mponce: Data sets and scripts, for the morning session

Data sets and scripts, for the morning session

2016 Ontario Summer School for High Performance Computing Central

2016-07-12T19:30:10Z

Mponce: /* Slides */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

* [https://support.scinet.utoronto.ca/~nolta/HPC_intro.pdf Slides]

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

* [[Media:intro_to_the_unix_shell.pdf | Slides ]]

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/b/b1/Intro_R.pdf Slides]

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====
* [[Media:MPIss2016.pdf | Slides ]]
----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

* [https://wiki.scinet.utoronto.ca/wiki/images/0/02/Parallel_R.pdf Slides]

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-I.pdf Morning Session]

[https://support.scinet.utoronto.ca/~mponce/ss2016/ss2016_visualization-II.pdf Afternoon Session]

======Datasets======
[ Morning datasets and scripts]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-11T12:18:13Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======
======Datasets======
[ Morning datasets and scripts]

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm dataset]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-11T12:17:31Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======
======Datasets======

[https://support.scinet.utoronto.ca/~mponce/ss2016/datasets.tar.gz Afternoon dataset]

[https://support.scinet.utoronto.ca/~mponce/ss2016/aneurysm_data.tar.gz Aneurysm data set]
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-10T15:45:51Z

Mponce: /* Datasets */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======
======Datasets======

----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-10T15:45:24Z

Mponce: /* Slides */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======
======Datasets======

==Datasets==
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-10T15:45:14Z

Mponce: /* Visualization */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
======Slides======
======Datasets======

==Slides==

==Datasets==
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-10T15:44:05Z

Mponce: /* Visualization */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M5S 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====
==Slides==

==Datasets==
----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-08T16:46:42Z

Mponce: /* Details */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M56 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 119 

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====

----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-08T16:29:37Z

Mponce: /* About */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

The location of this version of the summer school is:

'''Wallberg Building''' 
'''Rooms 116 and 119''' 
University of Toronto 
St. George Campus 
184-200 College Street 
Toronto, Ontario, M56 3E5 
Canada

More information can be found below and in the [[Media:handout2016.pdf|handout package]].

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

* [[Media:OpenMP2016.pdf | Slides]]
* [[Media:OpenMP_SS2015_code.tar.gz|Code]]

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

Wallberg Building, Room 116

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 116

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====

----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

Wallberg Building, Room 119

Note the different room number!

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

Wallberg Building, Room 119

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

SciNet User Support Library

2016-07-08T16:28:48Z

Mponce: /* Tutorials and Manuals */

__NOTOC__
{| style="border-spacing: 8px;"
| valign="top" style="cellpadding:1em; padding:1em; border:3px solid #0645ad; background-color:#f6f6f6; border-radius:7px"|
{{SciNetWiki:System_Alerts}}
| valign="top" style="cellpadding:1em; padding:1em; border:3px solid #0645ad; background-color:#f6f6f6; border-radius:7px"|
==System News==
* May 11: GPC: https://my.scinet.utoronto.ca/ is available for testing.

* May 3: GPC: Versions 15.0.6 and 16.0.3 of the Intel Compilers are installed as modules.

* Feb 12: GPC: Version 6.0 of Allinea Forge (DDT Debugger, MAP, Performance Reports) installed as a module.

* Jan 11: The 2016 Resource Allocations for compute cycles are now in effect.

* Nov 23: The quota for home directories has been increased from 10 GB to 50 GB.

* Nov 23, GPC: Two [[Visualization Nodes]], viz01 and viz02, are being setup. They are 8-core Nehalem nodes with 2 graphics cards each, 64 GB of memory, and about 60GB of local hard disk. For now, you can directly log into viz01 to try it out. We would value users' feedback and request for suitable software, help with visualization projects etc.

* Nov 16: ARC being decommissioned. During a transition period, the ARC head node and two compute nodes will be kept up. Users are encouraged to start using [[Gravity]] instead.

* Nov 12, GPC: The number of [[GPC_Quickstart#Compile.2FDevel_Nodes | GPC devel]] nodes has been doubled from 4 to 8, and the new ones can be accessed using gpc0[5-8].

* Nov 12, GPC: Two new [[GPC_Quickstart#Memory_Configuration| 128 GB RAM Haswell]] nodes have been added to the "largemem" queue.

* Sept 7, GPC: The number of nodes with [[GPC_Quickstart#Memory_Configuration|32 GB of RAM]] has been increased from 84 to 205.

* July 24, GPC: GCC 5.2.0 with [[Co-array_Fortran_on_the_GPC|Coarray Fortran]] support, installed as a module.

([[Previous System News]])
|-
| valign="top" width="50%" style="padding:1em; border:1px solid #aaaaaa; background-color:#f6e8e8; border-radius:7px" |

== QuickStart Guides ==
* [[SciNet Command Line Utilities]]
* [[Media:SciNet_Tutorial.pdf|SciNet User Tutorial]]
* [[GPC_Quickstart|GPC: General Purpose Cluster]]
* [[TCS_Quickstart|TCS: Tightly Coupled System]]
* [[Sandy| Sandy: Intel Sandybridge nodes ]]
* [[Gravity| Gravity: GPU nodes]]
* [[P7_Linux_Cluster|P7: Power 7 Linux cluster]]
* [[BGQ|BGQ: BlueGene/Q clusters]]
* [[Software_and_Libraries|Software and libraries]]
* [[Data_Management|Data management]]
* [[FAQ | FAQ (frequently asked questions)]]
* [[Acknowledging_SciNet | Acknowledging SciNet]]
* [[File:Rss.gif|link=http://support.scinet.utoronto.ca/podcasts.xml]] [http://support.scinet.utoronto.ca/podcasts.xml SciNet Training Webcasts]
| valign="top" style="padding:1em; border:1px solid #aaaaaa; background-color:#e8f6e8; border-radius:7px" |

== Tutorials and Manuals ==
* [[Knowledge_Base:_Tutorials_and_Manuals#SciNet_Basics|SciNet basics]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Linux|Linux]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Batch_job_management|Batch job management]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Programming|Programming]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Parallel_Programming|Parallel programming]]
* [[Knowledge_Base:_Tutorials_and_Manuals#GPU_Computing|GPU computing]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Performance_Tuning|Performance tuning]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Debugging|Debugging]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Math_libraries_.28BLAS.2C_LAPACK.2C_FFT.29|Math libraries (BLAS, LAPACK, FFT)]]
* [[Knowledge_Base:_Tutorials_and_Manuals#I/O|I/O and databases]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Visualization|Visualization]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Applications|Applications]]
* [[Knowledge_Base:_Tutorials_and_Manuals#Manuals|Manuals (compilers etc)]]
* [[2016_Ontario_Summer_School_for_High_Performance_Computing_Central]]
* [[2015_Ontario_Summer_School_for_High_Performance_Computing_Central]]
|-
| valign="top" style="padding:1em; border:1px solid #aaaaaa; background-color:#e8e8f6; border-radius:7px" |

== What's New On The Wiki ==
<div style='text-align:left;'>

* Dec 2014: Updated [[GPC Quickstart]] with info on email notifications from the scheduler.

* Dec 2014: [[Hdf5]] compilation page updated.

* Dec 2014: [[Research Computing with Python 2014]] lectures 5-8

* Nov 2014: "Modern CUDA Features" TechTalk slides in [[SciNet TechTalks and Seminars]].

* Nov 2014: [[Research Computing with Python 2014]] lectures 1-4

* Sept 2014: [[User_Tips#Reducing_virtual_memory_consumption_for_multithreaded_programs| Tip on reducing virtual memory consumption for multithreaded programs]]

* Sept 2014: Improved information on the [[Python]] versions installed on the GPC, and which modules are included in each version.

* Sept 2014: Description on using job arrays on the GPC on the [[Scheduler]] page.

* Sept 2014: [[Intro to Tkinter|Tkinter instructions]], [[Media:Tkinter.pdf|slides]] and [[Media:Tkinter_code.tgz|code]] for the TkInter workshop held in September.

* Sept 2014: Instructions on using [[Hadoop for HPCers|Hadoop]] (for the Hadoop workshop held in September).

</div>
Previous new stuff can be found in the [[What's new archive]].
| valign="top" style="padding:1em; border:1px solid #aaaaaa; background-color:#f4f4fa; border-radius:7px" |
<div style='text-align:left;'>
{{SciNetWiki:Community_Portal}}
</div>
|}

{{#Widget:Twitter|shell.background=#9fb1c2|tweets.links=#4775c1|tweets.color=#000000|tweets.background=#ffffff|user=SciNetHPC}}

<!-- [[Old Main Page]] --!>

2016 Ontario Summer School for High Performance Computing Central

2016-07-06T16:05:09Z

Mponce: /* Prerequisites */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Ramses von Zan (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace],[http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC],[http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====

----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

2016 Ontario Summer School for High Performance Computing Central

2016-07-06T16:03:57Z

Mponce: /* Prerequisites */

===About===

The 2016 Ontario Summer School on High Performance Computing, whose second installment of the year will be hosted by SciNet, provides attendees with opportunities to learn and share knowledge and experience in high performance and technical computing. The format: a five-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming, parallel data processing, and general purpose graphics processing unit programming.

Below are descriptions and course material for the Central version, given from July 11th to July 15th, 2016, in Toronto.

__TOC__

===Introduction to HPC and SciNet===

=====Abstract=====
This half-day session will provide an introduction to basic concepts of high-performance computing. It is intended to be a high level primer for those largely new to HPC, and serve as a foundation upon which to build over the coming days. Topics will include motivation for HPC, essential issues, problem characteristics as they apply to parallelism and a high level overview of parallel programming models. Strategies of running large sets of serial processes using e.g. GNU parallel, will also be presented.

=====Details=====
''Time/date''

Monday July 11, 2016, 09:30 - 12:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Mike Nolta (SciNet)

=====Prerequisites=====
Basic Linux skills are useful to follow along. If you do not have these, consider taking the "Intro to the Linux Shell" in the afternoon.

=====Slides and other material=====

----

===Programming Shared Memory Systems with OpenMP===

=====Abstract=====
In these two half-day sessions, lectures and hands-on labs are interspersed, and the students will learn the basics of shared memory programming with OpenMP. In particular, we will discuss the OpenMP's threads, memory, and performance, reductions and load balancing. We will also discuss extensions to heterogeneous systems such as offered by the OpenMP 4.0 and OpenACC standards.

=====Details=====

''Time/date''

Monday July 11, 2016, 13:30 - 16:30 
Tuesday July 12, 2016, 09:30 - 12:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Ramses van Zon (SciNet)

=====Prerequisites=====
C/C++ and/or Fortran scientific programming; Experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Introduction to the Linux Shell===

====Abstract====
Working with many of the HPC systems in Ontario involves using the Linux/UNIX command line. This provides a very powerful interface, but it can be quite daunting for the uninitiated. In this half-day session, you can become initiated with this course. This hands on session will cover basic commands and scripting, as well as touching on some powerful constructs like regular expressions. It could be a great boon for your productivity!

====Details====
''Time/date''

Monday July 11, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Mike Nolta (SciNet)

====Prerequisites====
A laptop with a linux-like environment.

====Slides and other material====

----

===R for Data Science===

=====Abstract=====
This session offers a brief introduction to R, with a focus on data analysis and statistics.

=====Details=====

''Date/time''

Tuesday July 12, 2016, 09:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====

Some programming experience in any language. You should have used and written functions. Bring a laptop with R or Rstudio installed.

=====Slides and other material=====

----

===Programming Clusters with MPI===

=====Abstract=====
In this 1.5-day session, through lectures interspersed with hands-on labs, the students will learn the basics of MPI programming. Examples and exercises will be based on parallelization of common scientific computing problems.

=====Details=====
''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30 
Wednesday July 13, 2016, 09:30 - 12:30 
Wednesday July 13, 2016, 13:30 - 16:30 

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Scott Northrup (SciNet)

=====Prerequisites=====
C and/or Fortran scientific programming; experience editing and compiling code in a Linux environment.

=====Slides and other material=====

----

===Parallel R for Data Science===

=====Abstract=====
This half-day session will cover parallel programming in R, with a focus on parallel data analysis. Topics covered will include snow, parallel, and foreach/doparallel.

=====Details=====

''Time/date''

Tuesday July 12, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
Experience with programming in R and a rudimentary understanding of parallel computing.

=====Slides and other material=====

----

===Python for Scientific Computing===

=====Abstract=====
In this half-day session, you will be taught how to use python for research computing purposes. Topics include: the basics of python, automation, numpy, scipy, file i/o, and visualization.

=====Details=====
''Time/date'''

Wednesday July 13, 9:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Erik Spence (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Python for High Performance Computing===

=====Abstract=====
This half-day session will cover parallel programming in python, with a focus on parallel data analysis. We will cover subprocess, multiprocessing, pypar and other parallel-enabling python packages.

=====Details=====
''Time/date''

Wednesday July 13, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''

Dr. Ramses von Zan (SciNet)

=====Prerequisites=====
A bit of coding experience in any programming or scripting language. Command-line experience in Linux is a plus.

=====Slides and other material=====

----

===Programming GPUs with CUDA===

=====Abstract=====
This two-day session is an introductory course covering programming and computing on GPUs - graphics processing units - which are an increasingly common presence in massively parallel computing architectures. This session will cover both of the available C-like programming frameworks: NVIDIA’s CUDA C. The basics of GPU programming will be covered, and students will work through a number of hands on examples. Demonstrations of profiling and debugging applications running on the GPU will also be included. The structuring of data and computations that makes full use of the GPU will be discussed in detail. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30 
Friday July 15, 2016, 09:30 - 12:30 
Friday July 15, 2016, 13:30 - 16:30

''Location''

MC 252 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''
Dr. Pawel Pomorski and Dr. Sergey Mashchenko (SHARCNET)

=====Prerequisites=====
C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

=====Slides and other materials=====

----

===Visualization===

=====Abstract=====
The first part of this whole-day session will be a basic introduction to general-purpose scientific visualization tools such as gnuplot, grace(xmgr), remote tools (tunneling, VNC), python's matplotlib, and examples from other. The afternoon part will be a mix of lecture and hands-on to introduce more specialized scientific visualization software such as vmd, paraview, and visit.

=====Details=====
''Time/date''

Thursday July 14, 2016, 09:30 - 12:30 
Thursday July 14, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructor''
Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Software installed, for the morning session: gnuplot, xmgr ([http://plasma-gate.weizmann.ac.il/Grace/ Grace][http://plasma-gate.weizmann.ac.il/Xmgr/ xmgr]), ssh (graphic client), your favorite vnc client (egs. [https://www.realvnc.com/download/viewer/ RealVNC][http://www.tightvnc.com/download.php TightVNC]), python and matplotlib ([http://matplotlib.org/ matplotlib]); afternoon session: ParaView ([http://www.paraview.org/download/ ParaView]) and VisIt ([https://wci.llnl.gov/simulation/computer-codes/visit/executables VisIt]).

=====Slides and other material=====

----

===Debugging===

=====Abstract=====
Debugging is an important step in developing a new code, or porting an old one to a new machine. In this half-day session, we will discuss the debugging of frequently encountered bugs in serial code with gdb and the debugging of parallel (MPI and threaded) codes with DDT on live systems.

=====Details=====
''Date/time''

Friday July 15, 09:30 - 12:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''

Dr. Marcelo Ponce (SciNet)

=====Prerequisites=====
Basic familiarity with a high-level language (C/C++/Fortran) as well as compiling and running programs via the command line environment on a HPC system.

=====Slides and other material=====

----

===Bring Your Own Code===

=====Abstract=====
The final afternoon of the summer school is your chance to get help with your own code from the SciNet software analysts. Bring your code, explain your problem or concerns, and we'll give you advice and work with you to try to improve it.

=====Details=====
''Date/time''

Friday July 15, 2016, 13:30 - 16:30

''Location''

MC 254 
5 King's College Road 
Toronto, ON M5S 3G8

''Instructors''

Various SciNet software analysts.

=====Prerequisites=====
None.

Oldwiki.scinet.utoronto.ca:System Alerts

2016-05-20T14:00:18Z

Mponce: /* System Status */

Oldwiki.scinet.utoronto.ca:System Alerts

2016-05-12T18:29:28Z

Mponce: /* System Status */

Oldwiki.scinet.utoronto.ca:System Alerts

2016-04-21T17:24:27Z

Mponce: /* System Status */