SciNet User Support Library

Welcome to the SciNet User Support library. Here you will find up-to-date manuals put together by SciNet staff and users, as well as links to external resources, to help you make use of SciNet resources for computational scientific discovery.

QuickStart Guides Essential Login Information GPC - General Purpose Cluster: Nehalem (x86_64) cluster running Linux TCS - Tightly Coupled System: IBM Power 6 system running AIX Storage at SciNet Data Transfer from SciNet Software & Libraries Job Scheduling System (Moab) A Performance Primer Frequently Asked Questions Performance & Debugging Tools: GPC Performance & Debugging Tools: TCS Acknowledging SciNet SciNet Accounts Application Process	Manuals IBM AIX Manuals: C: Compiler Reference, Optimization and Programming Guide, Language Reference. C++: Compiler Reference, Optimization and Programming Guide, Language Reference. FORTRAN: Compiler Reference, Optimization and Programming Guide, Language Reference. ESSL (High performance math library): Guide and Reference, Parallel ESSL Guide and Reference Application Performance Tuning and Optimization on POWER6 LoadLeveler: LoadLeveler Using and Administering Parallel Environment: Parallel Environment Operation and Use Adaptive Computing (Cluster Resources) Manuals: MOAB: Moab Workload Manager TORQUE: Torque Resource Manager Intel Manuals MKL: Intel(R) Math Kernel Library for Linux* OS User's Guide
Tutorials Workshops given at SciNet: SciNet Parallel Scientific Computing Workshop, Aug-Sep 2009 IBM AIX Workshop, Nov 2008 IBM MPI Workshop, Feb 2009 IBM Compiler Workshop, Feb 2009 Useful Links: LLNL MPI Tutorial - This tutorial by Blaise Barney was used as the basis for Kirk Jordan's MPI workshop at SciNet. It is well worth studying.
User-Supplied Content Share your expertise with the SciNet Community! Running specific codes on SciNet machines Tips for performance or convenience on SciNet machines Running serial batch jobs (including GNU parallel) Using the ramdisk on SciNet's GPC User-space perl modules Packing up large data sets and putting them on HPSS Remote batch