Difference between revisions of "GPU Devel Nodes"

Latest revision as of 19:26, 31 August 2018

WARNING: SciNet is in the process of replacing this wiki with a new documentation site. For current information, please go to https://docs.scinet.utoronto.ca

The ARC GPU have been decommisioned. The head node, arc01, is still up, however for GPU computations, users are encouraged to move to the Gravity cluster. For visualization, new Visualization Nodes are being setup.

@@ Line 1: / Line 1: @@
-{{Infobox Computer
+{| style="border-spacing: 8px; width:100%"
-|image=[[Image:GeForce_9800_GT_3qtr_low.png|center|300px|thumb]]
+| valign="top" style="cellpadding:1em; padding:1em; border:2px solid; background-color:#f6f674; border-radius:5px"|
-|name=GPU Development Cluster
+'''WARNING: SciNet is in the process of replacing this wiki with a new documentation site. For current information, please go to [https://docs.scinet.utoronto.ca https://docs.scinet.utoronto.ca]'''
-|installed=April 2011
+|}
-|operatingsystem= Linux
-|loginnode= arc01 (from <tt>login.scinet</tt>)
-|numberofnodes=8
-|rampernode=48 Gb
-|corespernode=8
-|interconnect=Infiniband
-|vendorcompilers=gcc,nvcc
-}}
-The Intel nodes have two 4 core Xeon X5550 2.67GHz CPU's with 48GB of RAM per node along with two NVIDIA M2070 (Fermi) GPU's each with 6 GB or RAM.
+<span style="color:#772222">The ARC GPU have been decommisioned. The head node, arc01, is still up, however for GPU computations, users are encouraged to move to the [[Gravity]] cluster.  For visualization, new [[Visualization Nodes]] are being setup.</span>
-===Login===
-First login via ssh with your scinet account at <tt>login.scinet.utoronto.ca</tt>, and from there you can proceed to <tt>ar01</tt> which
-is the GPU development node.
-Access to these machines is currently controlled. Please email support@scinet.utoronto.ca for access.
-==Compile/Devel/Compute Nodes==
-=== Nehalem (x86_64) ===
-=== Software ===
-The same software installed on the GPC is available on ARC using the same modules framework.
-See [[GPC_Quickstart#Modules_and_Environment_Variables | here]] for full details.
-=== Driver Version ===
-The current NVIDIA driver version installed is 270.40.
-==Programming Frameworks==
-Currently there are two programming frameworks to use, NVIDIA's CUDA framework or OpenCL.
-=== CUDA ===
-The current CUDA Toolkits in use are 3.0, 3.1, 3.2 (default) and 4.0. To use 3.2 just add the following module
-<pre>
-module load cuda/3.2
-</pre>
-Note that to use the full 6GB or memory per GPU, at least CUDA 3.2 must be used.
-The CUDA driver is installed locally, however the CUDA Toolkits are installed in.
-<pre>
-/project/scinet/arc/cuda-$VERSION/
-</pre>
-The variable $SCINET_CUDA_INSTALL is set when a cuda module is loaded and is pointed to the
-install location.  This is useful when setting up your makefile or if you use the NVIDIA_SDK
-makefiles modify the NVIDIA_SDK/C/common/common.mk file accordingly.
-<pre>
-CUDA_INSTALL_PATH ?= $SCINET_CUDA_INSTALL
-</pre>
-=== OpenCL ===
-As of 3.0, OpenCL is included in the CUDA Toolkit so loading the CUDA module is all the is required.
-===Compilers===
-* '''nvcc''' -- Nvidia compiler
-===MPI===
-The GPC MPI packages can be used on this system. See the GPC section on [[ GPC_Quickstart#MPI |MPI ]] for more details.
-== Documentation ==
-* CUDA
-** google "CUDA"
-* OpenCL
-** see above
-== Further Info ==
-== User Codes ==
-Please discuss put any relevant information/problems/best practices you have encountered when using/developing for CUDA and/or OpenCL

Difference between revisions of "GPU Devel Nodes"

Latest revision as of 19:26, 31 August 2018

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