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CUDA programming : a developer's guide to parallel computing with GPUs / Shane Cook.

By: Material type: TextPublication details: Amsterdam ; Boston : Elsevier, MK, c2013.Edition: 1stDescription: xiv, 576 p. : ill. ; 24 cmISBN:
  • 9780124159334
  • 0124159338
Subject(s): DDC classification:
  • 005.275 23
LOC classification:
  • QA76.76.A65 C668 2013
Online resources: Summary: "If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both. Detailed instructions help readers optimize the CUDA software development kit. Practical techniques illustrate working with memory, threads, algorithms, resources, and more. Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets. Each chapter includes exercises to test reader knowledge." --
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Books Centeral Library Second Floor - Computer Sciences 005.275 C.S.C 2013 (Browse shelf(Opens below)) Available 22042

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Includes bibliographical references and index.

"If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both. Detailed instructions help readers optimize the CUDA software development kit. Practical techniques illustrate working with memory, threads, algorithms, resources, and more. Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets. Each chapter includes exercises to test reader knowledge." --

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