Delivering faster results through parallelisation and GPU acceleration

Matthew Newall; Violeta Holmes; Colin Venters; Paul Lunn

doi:10.1007/978-3-319-14654-6_19

Delivering faster results through parallelisation and GPU acceleration

Matthew Newall, Violeta Holmes, Colin Venters, Paul Lunn

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

1 Citation (Scopus)

Abstract

The rate of scientific discovery depends on the speed at which accurate results and analysis can be obtained. The use of parallel co-processors such as Graphical Processing Units (GPUs) is becoming more and more important in meeting this demand as improvements in serial data processing speed become increasingly difficult to sustain. However, parallel data processing requires more complex programming compared to serial processing. Here we present our methods for parallelising two pieces of scientific software, leveraging multiple GPUs to achieve up to thirty times speed up.

Original language	English
Title of host publication	Intelligent Systems in Science and Information 2014
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Publisher	Springer, Cham
Pages	309-320
Number of pages	12
Volume	591
ISBN (Electronic)	9783319146546
ISBN (Print)	9783319146539, 9783319356785
DOIs	https://doi.org/10.1007/978-3-319-14654-6_19
Publication status	Published - 19 Mar 2015
Event	2014 Science and Information Conference - Park Inn by Radisson Hotel, London, United Kingdom Duration: 27 Aug 2014 → 29 Aug 2014 http://saiconference.com/Conferences/SAIConference2014 (Link to Conference Details )

Publication series

Name	Studies in Computational Intelligence
Publisher	Springer
Volume	591
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

Conference

Conference	2014 Science and Information Conference
Abbreviated title	SAI 2014
Country/Territory	United Kingdom
City	London
Period	27/08/14 → 29/08/14
Internet address	http://saiconference.com/Conferences/SAIConference2014 (Link to Conference Details )

Access to Document

10.1007/978-3-319-14654-6_19Licence: Unspecified

Cite this

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title = "Delivering faster results through parallelisation and GPU acceleration",

abstract = "The rate of scientific discovery depends on the speed at which accurate results and analysis can be obtained. The use of parallel co-processors such as Graphical Processing Units (GPUs) is becoming more and more important in meeting this demand as improvements in serial data processing speed become increasingly difficult to sustain. However, parallel data processing requires more complex programming compared to serial processing. Here we present our methods for parallelising two pieces of scientific software, leveraging multiple GPUs to achieve up to thirty times speed up.",

keywords = "CUDA, GPU, GPU cluster, Parallelisation",

author = "Matthew Newall and Violeta Holmes and Colin Venters and Paul Lunn",

year = "2015",

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booktitle = "Intelligent Systems in Science and Information 2014",

address = "Switzerland",

note = "2014 Science and Information Conference, SAI 2014 ; Conference date: 27-08-2014 Through 29-08-2014",

url = "http://saiconference.com/Conferences/SAIConference2014",

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Newall, M, Holmes, V, Venters, C & Lunn, P 2015, Delivering faster results through parallelisation and GPU acceleration. in K Arai, S Kapoor & R Bhatia (eds), Intelligent Systems in Science and Information 2014. vol. 591, Studies in Computational Intelligence, vol. 591, Springer, Cham, pp. 309-320, 2014 Science and Information Conference, London, United Kingdom, 27/08/14. https://doi.org/10.1007/978-3-319-14654-6_19

Delivering faster results through parallelisation and GPU acceleration. / Newall, Matthew; Holmes, Violeta; Venters, Colin et al.

Intelligent Systems in Science and Information 2014. ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Vol. 591 Springer, Cham, 2015. p. 309-320 (Studies in Computational Intelligence; Vol. 591).

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

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AU - Holmes, Violeta

AU - Venters, Colin

AU - Lunn, Paul

PY - 2015/3/19

Y1 - 2015/3/19

N2 - The rate of scientific discovery depends on the speed at which accurate results and analysis can be obtained. The use of parallel co-processors such as Graphical Processing Units (GPUs) is becoming more and more important in meeting this demand as improvements in serial data processing speed become increasingly difficult to sustain. However, parallel data processing requires more complex programming compared to serial processing. Here we present our methods for parallelising two pieces of scientific software, leveraging multiple GPUs to achieve up to thirty times speed up.

AB - The rate of scientific discovery depends on the speed at which accurate results and analysis can be obtained. The use of parallel co-processors such as Graphical Processing Units (GPUs) is becoming more and more important in meeting this demand as improvements in serial data processing speed become increasingly difficult to sustain. However, parallel data processing requires more complex programming compared to serial processing. Here we present our methods for parallelising two pieces of scientific software, leveraging multiple GPUs to achieve up to thirty times speed up.

KW - CUDA

KW - GPU

KW - GPU cluster

KW - Parallelisation

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DO - 10.1007/978-3-319-14654-6_19

M3 - Conference contribution

AN - SCOPUS:84922937926

SN - 9783319146539

SN - 9783319356785

VL - 591

T3 - Studies in Computational Intelligence

SP - 309

EP - 320

BT - Intelligent Systems in Science and Information 2014

A2 - Arai, Kohei

A2 - Kapoor, Supriya

A2 - Bhatia, Rahul

PB - Springer, Cham

T2 - 2014 Science and Information Conference

Y2 - 27 August 2014 through 29 August 2014

ER -

Delivering faster results through parallelisation and GPU acceleration

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