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Parallel Computer Architecture: A Hardware/Software Approach (The Morgan Kaufmann Series in Computer Architecture and Design), by David Cu
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The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions.
- synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development
- presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs
- describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies
- illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs
- Sales Rank: #939286 in Books
- Brand: Brand: Morgan Kaufmann
- Published on: 1998-08-15
- Original language: English
- Number of items: 1
- Dimensions: 9.28" h x 2.09" w x 7.62" l, 4.25 pounds
- Binding: Hardcover
- 1056 pages
- Used Book in Good Condition
From the Back Cover
The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions.
Features:
- synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development
- presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs
- describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies
- illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs
About the Author
David Culler led the Berkeley Network of Workstations (NOW) project, which sparked the current commercial revolution in high-performance clusters. Anoop Gupta co-led the Stanford DASH multiprocessor project, which developed the shared-memory technology increasingly used in commercial machines.
Jaswinder Pal Singh led the development of the SPLASH and SPLASH-2 suites of parallel programs, which have defined the workloads and methodology used to drive decisions and evaluate trade-offs in shared- memory parallel architecture.
Dr. Anoop Gupta is a Distinguished Scientist at Microsoft Research. He works on cross-disciplinary projects that have potential for large business or societal impact. His recent projects focus on areas of education, communication, collaboration, and natural user interfaces.
Most helpful customer reviews
3 of 4 people found the following review helpful.
Unsuitable as a Textbook
By Kindle Customer
This book appears to be an excellent *reference* in terms of extremely detailed aspects of parallel computing architectures.
However, as a textbook, it falls far short. The information presented in the text is an extremely difficult read (from a format perspective). The sample problems presented in the body of the text bear little or no relationship to the exercise at the end of each chapter. This makes it difficult or impossible to relate the exercises back to the information presented in the chapter. Since there is no answer key, you're left guessing if you've correctly answered them.
I find it baffling that anyone would use this text in a college classroom since it makes little or no effort to actually *teach* the material it presents.
0 of 1 people found the following review helpful.
A book with deep insight
By Bin Huang
The technology discussed in this book might be out-of-date but the framework that the authors use to design the system is worth learning. This book does require a good understanding on computer architecture. So it might not be suitable for you if you just start to learn this subject.
1 of 2 people found the following review helpful.
big and broad
By C. Kasper
Encyclopedic in scope and theory. Might be supplemented with more practical texts detailing
contemporary processors and code for Matlab/Simulink tools. Don't drop it on your toe!
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