Multi-Objective Differential Evolution on the GPU with C-CUDA

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86083948" target="_blank" >RIV/61989100:27240/12:86083948 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Objective Differential Evolution on the GPU with C-CUDA

Popis výsledku v původním jazyce

In some applications, evolutionary algorithms may require high computa- tional resources and high processing power, sometimes not producing a satisfactory solution after a running for a considerable amount of time. One possible improve- ment is a parallel approach to reduce the response time. This work proposes to study a parallel multi-objective algorithm, the multi-objective version of Differential Evo- lution (DE). The generation of trial individuals can be done in parallel, greatly re- ducing the overall processing time of the algorithm. A novel approach to parallelize this algorithm is the implementation on the Graphic Processing Units (GPU). These units present high degree of parallelism and they were initially developed for image rendering. However, NVIDIA has released a framework, named CUDA, which al- lows developers to use GPU for general-purpose computing (GPGPU). This work studies the implementation of Multi-Objective DE (MODE) on the GPU with C- CUDA, evaluating the gain i

Název v anglickém jazyce

Multi-Objective Differential Evolution on the GPU with C-CUDA

Popis výsledku anglicky

In some applications, evolutionary algorithms may require high computa- tional resources and high processing power, sometimes not producing a satisfactory solution after a running for a considerable amount of time. One possible improve- ment is a parallel approach to reduce the response time. This work proposes to study a parallel multi-objective algorithm, the multi-objective version of Differential Evo- lution (DE). The generation of trial individuals can be done in parallel, greatly re- ducing the overall processing time of the algorithm. A novel approach to parallelize this algorithm is the implementation on the Graphic Processing Units (GPU). These units present high degree of parallelism and they were initially developed for image rendering. However, NVIDIA has released a framework, named CUDA, which al- lows developers to use GPU for general-purpose computing (GPGPU). This work studies the implementation of Multi-Objective DE (MODE) on the GPU with C- CUDA, evaluating the gain i

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing

ISBN

978-3-642-32921-0

ISSN

2194-5357

e-ISSN

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Počet stran výsledku

10

Strana od-do

123 - 132

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Ostrava

Datum konání akce

5. 9. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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