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200 00$aGPU computing gems$b[electronic resource] /$feditor, Wen-mei W. Hwu
205   $aEmerald ed.
210   $aBurlington, Mass. $cElsevier$dc2011
215   $a1 online resource (889 p.)
225 0 $aMorgan Kaufmann's applications of GPU computing series
300   $aDescription based upon print version of record.
311   $a0-12-810182-2 
311   $a0-12-384988-8 
320   $aIncludes bibliographical references.
327   $asection 1. Scientific simulation -- section 2. Life sciences -- section 3. Statistical modeling -- section 4. Emerging data-intensive applications -- section 5. Electric design automation -- section 6. Ray tracing and rendering -- section 7. Computer vision -- section 8. Video and image processing -- section 9. Signal and audio processing -- section 10. Medical imaging.
330   $a""...the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk."" -Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010   Graphics processing units (GPUs) can do much more than render graphics. Scientists and researchers increasingly look to GPUs to improve the efficiency and performance of computationally-intensive experiments across a range of disciplines.    GPU Computing Gems: Emerald Edition brings their techniques to you, showcasing GPU-based solutions including:  Black hole simulations with CUDA
410  0$aApplications of GPU Computing Series
606   $aGraphics processing units$xProgramming
606   $aImaging systems
606   $aComputer graphics
606   $aImage processing$xDigital techniques
615  0$aGraphics processing units$xProgramming.
615  0$aImaging systems.
615  0$aComputer graphics.
615  0$aImage processing$xDigital techniques.
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