Abstract
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. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
El Zein, A., McCreath, E., Rendell, A., & Smola, A. (2008). Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5101 LNCS, pp. 466–475). https://doi.org/10.1007/978-3-540-69384-0_52
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