Scientific computation through a GPU

Genna Cummins; Rob Adams; Theodore Newell

doi:10.1109/SECON.2008.4494293

Scientific computation through a GPU

Genna Cummins, Rob Adams, Theodore Newell

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

4 Scopus citations

Abstract

A personal computer's graphics processing unit, or GPU, has been the seed of a growing interest in the academic and research communities of recent months. This paper investigates current technology that enables a GPU to process and solve linear algebra computations, in particular, matrix operations. Matrix operations of linear algebra are the basis of scientific computation, often used in modeling data and describing the forces of the universe. The author wished to compare the speed of the computation through the CPU and the GPU. Utilizing NVIDIA's CUDA technology, they demonstrated that calculations are preformed considerably faster through the GPU than through the CPU. The authors concluded that all computation in the research community has the potential to run significantly faster than current CPU's allow.

Original language	English
Title of host publication	IEEE SoutheastCon 2008
Pages	244-246
Number of pages	3
DOIs	https://doi.org/10.1109/SECON.2008.4494293
State	Published - 2008
Event	IEEE SoutheastCon 2008 - Huntsville, AL, United States Duration: Apr 3 2008 → Apr 6 2008

Publication series

Name	Conference Proceedings - IEEE SOUTHEASTCON
ISSN (Print)	0734-7502

Conference

Conference	IEEE SoutheastCon 2008
Country/Territory	United States
City	Huntsville, AL
Period	4/3/08 → 4/6/08

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/SECON.2008.4494293

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title = "Scientific computation through a GPU",

abstract = "A personal computer's graphics processing unit, or GPU, has been the seed of a growing interest in the academic and research communities of recent months. This paper investigates current technology that enables a GPU to process and solve linear algebra computations, in particular, matrix operations. Matrix operations of linear algebra are the basis of scientific computation, often used in modeling data and describing the forces of the universe. The author wished to compare the speed of the computation through the CPU and the GPU. Utilizing NVIDIA's CUDA technology, they demonstrated that calculations are preformed considerably faster through the GPU than through the CPU. The authors concluded that all computation in the research community has the potential to run significantly faster than current CPU's allow.",

author = "Genna Cummins and Rob Adams and Theodore Newell",

year = "2008",

doi = "10.1109/SECON.2008.4494293",

language = "English",

isbn = "9781424418848",

series = "Conference Proceedings - IEEE SOUTHEASTCON",

pages = "244--246",

booktitle = "IEEE SoutheastCon 2008",

note = "IEEE SoutheastCon 2008 ; Conference date: 03-04-2008 Through 06-04-2008",

}

TY - GEN

T1 - Scientific computation through a GPU

AU - Cummins, Genna

AU - Adams, Rob

AU - Newell, Theodore

PY - 2008

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N2 - A personal computer's graphics processing unit, or GPU, has been the seed of a growing interest in the academic and research communities of recent months. This paper investigates current technology that enables a GPU to process and solve linear algebra computations, in particular, matrix operations. Matrix operations of linear algebra are the basis of scientific computation, often used in modeling data and describing the forces of the universe. The author wished to compare the speed of the computation through the CPU and the GPU. Utilizing NVIDIA's CUDA technology, they demonstrated that calculations are preformed considerably faster through the GPU than through the CPU. The authors concluded that all computation in the research community has the potential to run significantly faster than current CPU's allow.

AB - A personal computer's graphics processing unit, or GPU, has been the seed of a growing interest in the academic and research communities of recent months. This paper investigates current technology that enables a GPU to process and solve linear algebra computations, in particular, matrix operations. Matrix operations of linear algebra are the basis of scientific computation, often used in modeling data and describing the forces of the universe. The author wished to compare the speed of the computation through the CPU and the GPU. Utilizing NVIDIA's CUDA technology, they demonstrated that calculations are preformed considerably faster through the GPU than through the CPU. The authors concluded that all computation in the research community has the potential to run significantly faster than current CPU's allow.

UR - http://www.scopus.com/inward/record.url?scp=50149119338&partnerID=8YFLogxK

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DO - 10.1109/SECON.2008.4494293

M3 - Conference contribution

AN - SCOPUS:50149119338

SN - 9781424418848

T3 - Conference Proceedings - IEEE SOUTHEASTCON

SP - 244

EP - 246

BT - IEEE SoutheastCon 2008

T2 - IEEE SoutheastCon 2008

Y2 - 3 April 2008 through 6 April 2008

ER -

Scientific computation through a GPU

Abstract

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ASJC Scopus subject areas

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