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Programming massively parallel proce...

Hwu, Wen-mei.

Programming massively parallel processors : = a hands-on approach /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Programming massively parallel processors :/ David B. Kirk and Wen-mei W. Hwu.
其他題名:	a hands-on approach /
作者:	Kirk, David,
其他作者:	Hwu, Wen-mei.
出版者:	San Francisco, Calif. :Morgan Kaufmann ; : 2013.,
面頁冊數:	xx, 496 p. :ill. ; : 23 cm.;
附註:	Previous edition: 2010.
標題:	Multiprocessors. -
ISBN:	9780124159921 (pbk.) :

Programming massively parallel processors : = a hands-on approach /
Kirk, David,1960-

Programming massively parallel processors :a hands-on approach /David B. Kirk and Wen-mei W. Hwu. - 2nd ed. - San Francisco, Calif. :Morgan Kaufmann ;2013. - xx, 496 p. :ill. ;23 cm.

Previous edition: 2010.

Includes bibliographical references and index.

History of GPU computing -- Introduction to data parallelism and CUDA C -- Data-parallel execution model -- CUDA memories -- Performance considerations -- Floating-point considerations -- Parallel patterns : convolution -- Parallel patterns : prefix sum -- Parallel patterns : sparse matric-vector multiplication -- Application case study : advanced MRI reconstruction -- Application case study : molecular visualization and analysis -- Parallel programming and computational thinking -- An introduction to OpenCL -- Parallel programming with OpenACC -- Thrust : a productivity-oriented library for CUDA -- CUDA FORTRAN -- An introduction to C++ AMP -- Programming a heterogeneous computing cluster -- CUDA dynamic parallelism -- Conclusion and future outlook.

This best-selling guide to CUDA and GPU parallel programming has been revised with more parallel programming examples, commonly-used libraries, and explanations of the latest tools. With these improvements, the book retains its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses. "Programming Massively Parallel Processors: A Hands-on Approach" shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Updates in this edition include: new coverage of CUDA 4.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.

ISBN: 9780124159921 (pbk.) :NT2252

Nat. Bib. No.: GBB2B1575bnbSubjects--Topical Terms:

636734
Multiprocessors.

LC Class. No.: QA76.642 / .K57 2013

Dewey Class. No.: 004.35

Programming massively parallel processors : = a hands-on approach /
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504 $a Includes bibliographical references and index.
505 0 # $a History of GPU computing -- Introduction to data parallelism and CUDA C -- Data-parallel execution model -- CUDA memories -- Performance considerations -- Floating-point considerations -- Parallel patterns : convolution -- Parallel patterns : prefix sum -- Parallel patterns : sparse matric-vector multiplication -- Application case study : advanced MRI reconstruction -- Application case study : molecular visualization and analysis -- Parallel programming and computational thinking -- An introduction to OpenCL -- Parallel programming with OpenACC -- Thrust : a productivity-oriented library for CUDA -- CUDA FORTRAN -- An introduction to C++ AMP -- Programming a heterogeneous computing cluster -- CUDA dynamic parallelism -- Conclusion and future outlook.
520 # $a This best-selling guide to CUDA and GPU parallel programming has been revised with more parallel programming examples, commonly-used libraries, and explanations of the latest tools. With these improvements, the book retains its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses. "Programming Massively Parallel Processors: A Hands-on Approach" shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Updates in this edition include: new coverage of CUDA 4.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.
650 # 0 $a Multiprocessors. $3 636734
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700 1 # $a Hwu, Wen-mei. $3 873849