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You'll find the CUDA toolkit in /opt/shared/cudatoolkit and the GPU computing SDK in /opt/shared/gpucomputingsdk. The SDK contains a number of CUDA sample C applications that can be found at /opt/shared/gpucomputingsdk/4.02.179/C. Compiled samples can be found in /opt/shared/gpucomputingsdk/4.02.179/C/bin/linux/release.
To support GPU access new LSF GPU queues have been installed: short_gpu, normal_gpu and long_gpu.
For example to run one of the compiled cuda codes:
> cp /opt/shared/gpucomputingsdk/4.02.179/C/bin/linux/release/simpleStreams .
> module load cuda
> bsub -q short_gpu -Ip -R "rusage [n_gpu_jobs=1 ]" ./simpleStreams
To view a description of sample codes cuda codes from the command line:
> lynx file:///opt/shared/gpucomputingsdk/4.02.179/C/Samples.html
or
> firefox file:///opt/shared/gpucomputingsdk/4.0.17/C/Samples.html
The name of the cuda compiler is nvcc and other tools can be found in:
/opt/shared/cudatoolkit/4.02.179/cuda/bin
The nvcc help file is obtained:
> nvcc -h
Also, you can view local cuda pdf docs on the cluster:
> evince /opt/shared/gpucomputingsdk/4.02.179/C/doc/programming_guide/CUDA_C_Programming_Guide.pdf
Other pdf documents in:
/opt/shared/cudatoolkit/4.02.179/cuda/doc/ and /opt/shared/gpucomputingsdk/4.02.179/C/doc/
Matlab GPU
A nice introductory article from Desktop Engineering of Matlab's GPU capability can be found here.
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