...
Another resource, Designing and Building Parallel Programs may be useful.
*Some additional supporting info on a parallel computing course can be found on this Tufts Computer Science link.
Interesting Intel thread parallelism links and codes
Threading Building Blocks
...
How does one find out gpu specific info?
> bsub -Ip -q short_gpu /opt/shared/gpucomputingsdk/4.2.9/C/bin/linux/release/deviceQuery
Another option:
> bsub -q short_gpu -o gpu_info.txt nvidia-smi -a
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/4.2.9/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/4.2.9/C/Samples.html
or
> firefox file:///opt/shared/gpucomputingsdk/4.0.17/C/Samples.html
...
Also, you can view local cuda pdf docs on the cluster using evince:
> evince /opt/shared/gpucomputingsdk/4.2.9/C/doc/programming_guide/CUDA_C_Programming_Guide.pdf
...
For example, to run Matlab and access GPU resources:
> module load matlab
> bsub -q short_gpu -Ip -R "rusage [n_gpu_jobs=1 ]" matlab
Additional GPU resources
There are many Cuda programming resources on the web and of course the Nvidia Cuda website.
...