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GPU Productivity Environment

GPU productivity environments have recently become an important part of scientific computing and visualization. The following is an attempt to define which ones are relevant for the LinkSCEEM-2 community and set an action plan.

BC Policy: LS2_11-99
Date of Policy: 1st January 2012
First Update: 1st December 2011
Second Update: 2nd December 2011

The main objective of this policy is to provide the following common GPU productivity environment across all LinkSCEEM-2 resources:

Package/Tool Requested version(s) Compliance level Reference
CUDA Toolkit v4.0 MUST http://developer.nvidia.com/cuda-toolkit-40
pyCUDA 2011.2.1 MUST http://mathema.tician.de/software/pycuda
pyOpenCL 2011.2 MUST http://mathema.tician.de/software/pyopencl
MAGMA v1.1 MUST http://icl.cs.utk.edu/magma/
ViennaCL 1.2.0 MUST http://viennacl.sourceforge.net/
AMD math library for OpenCL (APPML) v1.4 MUST http://developer.amd.com/libraries/appmathlibs/Pages/default.aspx
Intel OpenCL SDK v1.5 SHOULD http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/
CULA r12 SHOULD http://www.culatools.com/
gputools R package v0.26 SHOULD http://cran.r-project.org/web/packages/gputools/index.html
rCUDA v3.1 SHOULD http://www.rCUDA.net

These GPU productivity environment will be supplemented with other such productivity tools as they become available on allocated systems.

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