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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. We have implemented several possible solutions that use different memory access schemes. Detailed evaluation is provided in this paper where the obtained results show a tremendous processing s
  • 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. We have implemented several possible solutions that use different memory access schemes. Detailed evaluation is provided in this paper where the obtained results show a tremendous processing s (en)
Title
  • Towards Accelerated Computation of Atmospheric Equations using CUDA
  • Towards Accelerated Computation of Atmospheric Equations using CUDA (en)
skos:prefLabel
  • Towards Accelerated Computation of Atmospheric Equations using CUDA
  • Towards Accelerated Computation of Atmospheric Equations using CUDA (en)
skos:notation
  • RIV/00216305:26230/09:PU82579!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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  • 346553
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/09:PU82579
http://linked.open...riv/jazykVysledku
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  • CUDA, GPU, advection-diffusion equation, partial differential equation, Runge-Kutta, CFD (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [4D5F694C765F]
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  • Cambridge
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  • Cambridge
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  • Proceedings of Eleventh International Conference on Computer Modelling and Simulation
http://linked.open...in/vavai/riv/obor
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http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Dvořák, Radim
  • Kunovský, Jiří
  • Zbořil, František
  • Šimek, Václav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • IEEE Computer Society
https://schema.org/isbn
  • 978-0-7695-3593-7
http://localhost/t...ganizacniJednotka
  • 26230
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