Can the performance of GPGPU really beat CPU in evolutionary design task?

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F08%3APU78069" target="_blank" >RIV/00216305:26230/08:PU78069 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Can the performance of GPGPU really beat CPU in evolutionary design task?

Original language description

With the appearance of modern general purpose graphical processor units (GPU), a powerful and cheap architecture has entered the field of scientific computation. This highly parallel architecture, formerly designed for floating point graphical operationacceleration, is now being used for the acceleration of<br>various algorithms. <br><br>During the past few years, various papers dealing with the utilization of GPUs in general purpose computing have been published. Even evolutionary algorithms have beenaccelerated [1, 3], among them genetic programming and its variants. In order to achieve maximal performance of genome evaluation, various approaches of candidate solution evaluation have been proposed. The genome can be evaluated as a program which canbe directly downloaded into the GPU [1] or interpreted by using an interpreter program running on the GPU [2]. Due to the architectural limitations, the second method appears to be more promising in comparison with the previous one.<br><

Czech name

Can the performance of GPGPU really beat CPU in evolutionary design task?

Czech description

With the appearance of modern general purpose graphical processor units (GPU), a powerful and cheap architecture has entered the field of scientific computation. This highly parallel architecture, formerly designed for floating point graphical operationacceleration, is now being used for the acceleration of<br>various algorithms. <br><br>During the past few years, various papers dealing with the utilization of GPUs in general purpose computing have been published. Even evolutionary algorithms have beenaccelerated [1, 3], among them genetic programming and its variants. In order to achieve maximal performance of genome evaluation, various approaches of candidate solution evaluation have been proposed. The genome can be evaluated as a program which canbe directly downloaded into the GPU [1] or interpreted by using an interpreter program running on the GPU [2]. Due to the architectural limitations, the second method appears to be more promising in comparison with the previous one.<br><

Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

—

Project

—

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2008

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

4th Doctoral Workshop on Mathematical and Engineering Methods in Computer Science

ISBN

978-80-7355-082-0

ISSN

—

e-ISSN

—

Number of pages

1

Pages from-to

—

Publisher name

Masaryk University

Place of publication

Znojmo

Event location

Znojmo

Event date

Nov 14, 2008

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—