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  • 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 primarily based
  • 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 primarily based (en)
Title
  • GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations
  • GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations (en)
skos:prefLabel
  • GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations
  • GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations (en)
skos:notation
  • RIV/00216305:26230/09:PU82615!RIV10-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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  • 316599
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/09:PU82615
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  • CUDA, GPU, advection-diffusion equation, partial differential equation, Runge-Kutta, acceleration (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [ADEB82616AE5]
http://linked.open...v/mistoKonaniAkce
  • Patras
http://linked.open...i/riv/mistoVydani
  • Patras
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  • 12th EUROMICRO Conference on Digital System Design DSD 2009
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http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Dvořák, Radim
  • Zbořil, František
  • Šimek, Václav
  • Drábek, Vladimír
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 978-0-7695-3277-6
http://localhost/t...ganizacniJednotka
  • 26230
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