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  • In many research fields the numerical problems demand extremely large computational power. As a consequence, researchers are constantly demanding new and more powerful computers. Recently, the graphics chip producer NVIDIA launched the CUDA parallel computing architecture, which enables scientists to utilize the extreme power available on modern and relatively cheap Graphical Processor Units (GPUs). Necessity to change the common approach together with significant difference in the GPU architecture prevents the wide usage of the graphics hardware.
  • In many research fields the numerical problems demand extremely large computational power. As a consequence, researchers are constantly demanding new and more powerful computers. Recently, the graphics chip producer NVIDIA launched the CUDA parallel computing architecture, which enables scientists to utilize the extreme power available on modern and relatively cheap Graphical Processor Units (GPUs). Necessity to change the common approach together with significant difference in the GPU architecture prevents the wide usage of the graphics hardware. (en)
Title
  • GPU computation in engineering practice
  • GPU computation in engineering practice (en)
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  • GPU computation in engineering practice
  • GPU computation in engineering practice (en)
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  • RIV/68378297:_____/11:00359903!RIV12-AV0-68378297
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  • P(IAA200710805), Z(AV0Z20710524)
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  • 201460
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  • RIV/68378297:_____/11:00359903
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  • numericsl computation; GPU; CUDA (en)
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  • [E6EC23620E27]
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  • Svratka
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  • Prague
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  • Engineering Mechanics 2011
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  • Fischer, Cyril
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  • Ústav termomechaniky AV ČR
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  • 978-80-87012-33-8
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