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Common GPU Productivity Environments

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 environments across all LinkSCEEM-2 resources:

CUDA Toolkit CUDA Toolkit MUST
pyCUDA 2011.2 pyCUDA 2011.2 MUST
pyOpenCL 2011.2 pyOpenCL 2011.2 MUST
MAGMA v1.1 MAGMA v1.1 MUST
ViennaCL 1.2.0 ViennaCL 1.2.0 MUST
AMD math library for OpenCL (APPML) AMD math library for OpenCL (APPML) MUST
Intel OpenCL SDK Intel OpenCL SDK MUST
CULA CULA SHOULD
gputools R package gputools R package SHOULD
rCUDA rCUDA SHOULD

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

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