GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F09%3APU82615" target="_blank" >RIV/00216305:26230/09:PU82615 - 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

GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Popis výsledku v původním jazyce

Main objective of this paper is to outline possible ways how to achieve a substantial acceleration in case of advection-diffusion equation (A-DE) calculation, which is commonly used for a description of the pollutant behavior in atmosphere. A-DE is a kind of partial differential equation (PDE) and in general case it is usually solved by numerical integration due to its high complexity. These types of calculations are time consuming thus the main idea of our work is to adopt CUDA platform and commodity GPU card to do the calculations in a faster way. The solution is based on method of lines with 4th order Runge-Kutta scheme to handle the integration. As a matter of fact, the selected approach involves number of auxiliary variables and thus the memory management is critical in order to achieve desired performance. From a technical point of view, we have implemented a particular variant of the A-DE system, where the pollutant concentration is time-dependent. An efficient data handling is

Název v anglickém jazyce

GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Popis výsledku anglicky

Main objective of this paper is to outline possible ways how to achieve a substantial acceleration in case of advection-diffusion equation (A-DE) calculation, which is commonly used for a description of the pollutant behavior in atmosphere. A-DE is a kind of partial differential equation (PDE) and in general case it is usually solved by numerical integration due to its high complexity. These types of calculations are time consuming thus the main idea of our work is to adopt CUDA platform and commodity GPU card to do the calculations in a faster way. The solution is based on method of lines with 4th order Runge-Kutta scheme to handle the integration. As a matter of fact, the selected approach involves number of auxiliary variables and thus the memory management is critical in order to achieve desired performance. From a technical point of view, we have implemented a particular variant of the A-DE system, where the pollutant concentration is time-dependent. An efficient data handling is

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

12th EUROMICRO Conference on Digital System Design DSD 2009

ISBN

978-0-7695-3277-6

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

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Název nakladatele

IEEE Computer Society

Místo vydání

Patras

Místo konání akce

Patras

Datum konání akce

27. 8. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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