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

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

doi:10.1007/978-3-540-69384-0_52

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

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 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 language	English
Title of host publication	Computational Science - ICCS 2008 - 8th International Conference, Proceedings
Pages	466-475
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-540-69384-0_52
Publication status	Published - 2008
Event	8th International Conference on Computational Science, ICCS 2008 - Krakow, Poland Duration: 23 Jun 2008 → 25 Jun 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	5101 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Computational Science, ICCS 2008
Country/Territory	Poland
City	Krakow
Period	23/06/08 → 25/06/08

Access to Document

10.1007/978-3-540-69384-0_52

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

El Zein, Ahmed ; McCreath, Eric ; Rendell, Alistair et al. / Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning. Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 1. ed. 2008. pp. 466-475 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning",

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.",

author = "{El Zein}, Ahmed and Eric McCreath and Alistair Rendell and Alex Smola",

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doi = "10.1007/978-3-540-69384-0_52",

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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 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5101 LNCS, pp. 466-475, 8th International Conference on Computational Science, ICCS 2008, Krakow, Poland, 23/06/08. https://doi.org/10.1007/978-3-540-69384-0_52

Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning. / El Zein, Ahmed; McCreath, Eric; Rendell, Alistair et al.
Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 1. ed. 2008. p. 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Rendell, Alistair

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AB - 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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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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El Zein A, McCreath E, Rendell A, Smola A. Performance evaluation of the NVIDIA GeForce 8800 GTX GPU for machine learning. In Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 1 ed. 2008. p. 466-475. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-69384-0_52

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

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