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Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning

A El Zein, E McCreath, Alistair Rendell, Alex Smola
Australian National University
Computational Science-ICCS 2008 (2008) Volume: 5101, Issue: Ml, Publisher: Springer, Pages: 466-475

@article{el2008performance,

   title={Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning},

   author={El Zein, A. and Mccreath, E. and Rendell, A. and Smola, A.},

   journal={Computational Science–ICCS 2008},

   pages={466–475},

   year={2008},

   publisher={Springer}

}

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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.
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