Programming massively parallel processors:
By: Kirk, David B
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Material type: 
BookPublisher: New Delhi : Elsevier, 2015Description: 496 pages.ISBN: 9789351070443.Subject(s): Software Engineering Computer ScienceDDC classification: 004.35 Online resources: (Click here to access full-text book) | Item type | Current location | Call number | Copy number | Status | Date due | Barcode | Item holds |
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Learning Resource Center University of Management and Technology, Sialkot Iqbal Campus
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004.35 KIR-P 2015 4560 (Browse shelf) | C.1 | Available | 4560 | ||
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Learning Resource Center University of Management and Technology, Sialkot Iqbal Campus
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004.35 KIR-P 2015 9652 (Browse shelf) | C.2 | Available | 9652 | |||
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Learning Resource Center University of Management and Technology, Sialkot Iqbal Campus
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004.35 KIR-P 2015 10088 (Browse shelf) | C.3 | Available | 10088 |
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| 004.35 CUL-P Parallel computer architecture: | 004.35 CUL-P 2015 10069 Parallel computer architecture: | 004.35 KIR-P 2015 10088 Programming massively parallel processors: | 004.35 KIR-P 2015 4560 Programming massively parallel processors: | 004.35 KIR-P 2015 9652 Programming massively parallel processors: | 004.35 PAC-I 2011 10170 An introduction to parallel programming / | 004.35 ROS-U Understanding concurrent systems |
Chapter 1. Introduction
1.1 Heterogeneous Parallel Computing
1.2 Architecture of a Modern GPU
1.3 Why More Speed or Parallelism?
1.4 Speeding Up Real Applications
1.5 Parallel Programming Languages and Models
1.6 Overarching Goals
1.7 Organization of the Book
References
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.
This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, 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 (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.
This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers.
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