Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning
NVIDIA have released a new platform (CUDA) for general purpose computing on their graphical processing units (GPU). This paper evaluates use of this platform for statistical machine learning applications. The transfer rates to and from the GPU are measured, as is the performance of matrix vector operations on the GPU. An implementation of a sparse matrix vector product on the GPU is outlined and evaluated. Performance comparisons are made with the host processor.
|Collections||ANU Research Publications|
|Source:||Proceedings of the 2008 IEEE International Conference on Communication Systems|
|01_El Zein_Performance_Evaluation_of_the_2008.pdf||424.38 kB||Adobe PDF||Request a copy|
|02_El Zein_Performance_Evaluation_of_the_2008.pdf||493.31 kB||Adobe PDF||Request a copy|
|03_El Zein_Performance_Evaluation_of_the_2008.pdf||411.88 kB||Adobe PDF||Request a copy|
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