GPU Particle Swarm Optimization Applied to Travelling Salesman Problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86100170" target="_blank" >RIV/61989100:27240/15:86100170 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/MCSoC.2015.18" target="_blank" >http://dx.doi.org/10.1109/MCSoC.2015.18</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MCSoC.2015.18" target="_blank" >10.1109/MCSoC.2015.18</a>

Jazyk výsledku

angličtina

Název v původním jazyce

GPU Particle Swarm Optimization Applied to Travelling Salesman Problem

Popis výsledku v původním jazyce

Recently, the Graphic Processing Unit (GPUs) are used as an exciting new hardware environment for truly parallel implementation and execution of nature and Bio-inspired algorithms thanks to their excellent price-to-power ratio. Indeed, they are represented by the software platform using compute unified device architecture from NVIDIA, and the one of particle swarm optimization (PSO) which can be executed simultaneously on GPUs to speed up complex optimization problems such as Travelling Salesman Problem (TSP). In this paper, we illustrate a novel parallel approach to run standard particle swarm optimization PSO on GPUs and applied to TSP (GPU-PSO-A-TSP). Both the developed and the previous PSO centroid algorithm are implemented on the GPUs. The achieved results show that we have obtained at least one order of magnitude difference between speed of the GPUs and a typical sequential CPU implementation for performance optimization. Results show also that running speed of GPU-PSO is four times as fast as that of CPUP-SO.

Název v anglickém jazyce

GPU Particle Swarm Optimization Applied to Travelling Salesman Problem

Popis výsledku anglicky

Recently, the Graphic Processing Unit (GPUs) are used as an exciting new hardware environment for truly parallel implementation and execution of nature and Bio-inspired algorithms thanks to their excellent price-to-power ratio. Indeed, they are represented by the software platform using compute unified device architecture from NVIDIA, and the one of particle swarm optimization (PSO) which can be executed simultaneously on GPUs to speed up complex optimization problems such as Travelling Salesman Problem (TSP). In this paper, we illustrate a novel parallel approach to run standard particle swarm optimization PSO on GPUs and applied to TSP (GPU-PSO-A-TSP). Both the developed and the previous PSO centroid algorithm are implemented on the GPUs. The achieved results show that we have obtained at least one order of magnitude difference between speed of the GPUs and a typical sequential CPU implementation for performance optimization. Results show also that running speed of GPU-PSO is four times as fast as that of CPUP-SO.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

International symposium on embedded multicore/manycore systems-on-chip (MCSoC) : proceedings

ISBN

978-1-4799-8670-5

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

112-119

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Turín

Datum konání akce

23. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380390400015