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CUDA by example: an introduction to general- purpose GPU programming

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Chennai Pearson India Education Services Pvt. Ltd. 2023Description: xix, 290pISBN:
  • 9780131387683
  • 0131387685
  • 9789353434274
  • 9353434270
Subject(s): DDC classification:
  • 005.275 SAN-C
Summary: “This book is required reading for anyone working with accelerator-based computing systems.” –From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA.
Item type: Books and Monographs List(s) this item appears in: List of New Arrivals (Books)
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Item type Current library Home library Collection Call number Materials specified Status Date due Barcode
Books and Monographs Central Library, NIT Jalandhar General Stacks Central Library, NIT Jalandhar Center for Artificial Intelligence 005.275 SAN-C (Browse shelf(Opens below)) Available 102880
Books and Monographs Central Library, NIT Jalandhar General Stacks Central Library, NIT Jalandhar Center for Artificial Intelligence 005.275 SAN-C (Browse shelf(Opens below)) Available 102881
Books and Monographs Central Library, NIT Jalandhar General Stacks Central Library, NIT Jalandhar Center for Artificial Intelligence 005.275 SAN-C (Browse shelf(Opens below)) Available 102882
Books and Monographs Central Library, NIT Jalandhar General Stacks Central Library, NIT Jalandhar Center for Artificial Intelligence 005.275 SAN-C (Browse shelf(Opens below)) Available 102883

“This book is required reading for anyone working with accelerator-based computing systems.” –From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA.

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