Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning

Ahmed El Zein, Eric McCreath, Alistair Rendell, Alex Smola

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2008 - 8th International Conference, Proceedings
Pages466-475
Number of pages10
EditionPART 1
DOIs
Publication statusPublished - 28 Jul 2008
Externally publishedYes
Event8th International Conference on Computational Science, ICCS 2008 - Krakow, Poland
Duration: 23 Jun 200825 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5101 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Computational Science, ICCS 2008
CountryPoland
CityKrakow
Period23/06/0825/06/08

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  • Cite this

    El Zein, A., McCreath, E., Rendell, A., & Smola, A. (2008). Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning. In Computational Science - ICCS 2008 - 8th International Conference, Proceedings (PART 1 ed., pp. 466-475). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5101 LNCS, No. PART 1). https://doi.org/10.1007/978-3-540-69384-0_52