GPU computing gems:
" ... 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) are designed to be parallel - having hundreds of cores versus traditional CPUs. Inc...
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Burlington, MA
Morgan Kaufmann/Elsevier
© 2011
|
| Ausgabe: | Emerald ed |
| Schriftenreihe: | Applications of GPU computing
|
| Schlagworte: | |
| Online-Zugang: | FLA01 URL des Erstveröffentlichers |
| Zusammenfassung: | " ... 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) are designed to be parallel - having hundreds of cores versus traditional CPUs. Increasingly, you can leverage GPU power for many computationally-intense applications - not just for graphics. If you're facing the challenge of programming systems to effectively use these massively parallel processors to achieve efficiency and performance goals, GPU Computing Gems provides a wealth of tested, proven GPU techniques. Different application domains often pose similar algorithm problems, and researchers from diverse application domains often develop similar algorithmic strategies. GPU Computing Gems offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's Applications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 online resource (xx, 865 pages) illustrations |
| ISBN: | 9780123849885 0123849888 9780123849892 0123849896 |
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| spelling | GPU computing gems [edited by] Wen-mei W. Hwu Emerald ed Burlington, MA Morgan Kaufmann/Elsevier © 2011 1 online resource (xx, 865 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Applications of GPU computing Includes bibliographical references and index " ... 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) are designed to be parallel - having hundreds of cores versus traditional CPUs. Increasingly, you can leverage GPU power for many computationally-intense applications - not just for graphics. If you're facing the challenge of programming systems to effectively use these massively parallel processors to achieve efficiency and performance goals, GPU Computing Gems provides a wealth of tested, proven GPU techniques. Different application domains often pose similar algorithm problems, and researchers from diverse application domains often develop similar algorithmic strategies. GPU Computing Gems offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's Applications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing. Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use Computer graphics fast Image processing / Digital techniques fast Imaging systems fast Graphics processing units Programming Imaging systems Computer graphics Image processing Digital techniques Parallelverarbeitung (DE-588)4075860-6 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf CUDA Informatik (DE-588)7719528-0 gnd rswk-swf Grafikprozessor (DE-588)4582114-8 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Grafikprozessor (DE-588)4582114-8 s Bildverarbeitung (DE-588)4006684-8 s Parallelverarbeitung (DE-588)4075860-6 s 2\p DE-604 CUDA Informatik (DE-588)7719528-0 s 3\p DE-604 Hwu, Wen-mei edt http://www.sciencedirect.com/science/book/9780123849885 Verlag URL des Erstveröffentlichers Volltext data file rda 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | GPU computing gems Computer graphics fast Image processing / Digital techniques fast Imaging systems fast Graphics processing units Programming Imaging systems Computer graphics Image processing Digital techniques Parallelverarbeitung (DE-588)4075860-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd CUDA Informatik (DE-588)7719528-0 gnd Grafikprozessor (DE-588)4582114-8 gnd |
| subject_GND | (DE-588)4075860-6 (DE-588)4006684-8 (DE-588)7719528-0 (DE-588)4582114-8 (DE-588)4143413-4 |
| title | GPU computing gems |
| title_auth | GPU computing gems |
| title_exact_search | GPU computing gems |
| title_full | GPU computing gems [edited by] Wen-mei W. Hwu |
| title_fullStr | GPU computing gems [edited by] Wen-mei W. Hwu |
| title_full_unstemmed | GPU computing gems [edited by] Wen-mei W. Hwu |
| title_short | GPU computing gems |
| title_sort | gpu computing gems |
| topic | Computer graphics fast Image processing / Digital techniques fast Imaging systems fast Graphics processing units Programming Imaging systems Computer graphics Image processing Digital techniques Parallelverarbeitung (DE-588)4075860-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd CUDA Informatik (DE-588)7719528-0 gnd Grafikprozessor (DE-588)4582114-8 gnd |
| topic_facet | Computer graphics Image processing / Digital techniques Imaging systems Graphics processing units Programming Image processing Digital techniques Parallelverarbeitung Bildverarbeitung CUDA Informatik Grafikprozessor Aufsatzsammlung |
| url | http://www.sciencedirect.com/science/book/9780123849885 |
| work_keys_str_mv | AT hwuwenmei gpucomputinggems |