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  • Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control the casting process and to monitor the steel production. Moreover, these models of transient temperature field can also be utilized for optimization of continuous casting, its on-line regulation, or may help operators to solve non-standard or breakdown situations that can occur when casting. In order to solve these problems in real time, parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on CPUs. The paper describes an implementation of the parallel dynamic solidification model with the use of the CUDA architecture and NVIDIA GPUs. A comparison between the use of parallel and non-parallel models is presented and analysed. Results show that parallel computing on GPUs can considerably e
  • Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control the casting process and to monitor the steel production. Moreover, these models of transient temperature field can also be utilized for optimization of continuous casting, its on-line regulation, or may help operators to solve non-standard or breakdown situations that can occur when casting. In order to solve these problems in real time, parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on CPUs. The paper describes an implementation of the parallel dynamic solidification model with the use of the CUDA architecture and NVIDIA GPUs. A comparison between the use of parallel and non-parallel models is presented and analysed. Results show that parallel computing on GPUs can considerably e (en)
Title
  • Parallel dynamic solidification model of continuous steel casting on GPU
  • Parallel dynamic solidification model of continuous steel casting on GPU (en)
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  • Parallel dynamic solidification model of continuous steel casting on GPU
  • Parallel dynamic solidification model of continuous steel casting on GPU (en)
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  • RIV/00216305:26210/13:PU103650!RIV14-GA0-26210___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED0002/01/01), P(GAP107/11/1566), S
http://linked.open...vai/riv/dodaniDat
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  • 95292
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26210/13:PU103650
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  • dynamic solidification model, continuous casting, GPU, GPGPU, parallel computing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [DD9AB88A3FDB]
http://linked.open...v/mistoKonaniAkce
  • Brno
http://linked.open...i/riv/mistoVydani
  • Ostrava
http://linked.open...i/riv/nazevZdroje
  • Conference proceedings of 22nd Conference on metallurgy and materials
http://linked.open...in/vavai/riv/obor
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http://linked.open...vavai/riv/projekt
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http://linked.open...iv/tvurceVysledku
  • Klimeš, Lubomír
  • Štětina, Josef
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • Tanger s.r.o.
https://schema.org/isbn
  • 978-80-87294-39-0
http://localhost/t...ganizacniJednotka
  • 26210
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