Programming Massively Parallel Processors: A Hands-on Approach |  | Authors: David B. Kirk, Wen-mei W. Hwu
Publisher: Morgan Kaufmann
Category: Book
List Price: $69.95
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Rating:  6 reviews
Sales Rank: 2022
Media: Paperback
Edition: 1
Pages: 280
Number Of Items: 1
Shipping Weight (lbs): 1.3
Dimensions (in): 9.2 x 7.4 x 0.8
ISBN: 0123814723
Dewey Decimal Number: 004.35
EAN: 9780123814722
ASIN: 0123814723
Publication Date: February 5, 2010
Availability: Usually ships in 1-2 business days
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Product Description
Multi-core processors are no longer the future of computing-they are the present day reality. A typical mass-produced CPU features multiple processor cores, while a GPU (Graphics Processing Unit) may have hundreds or even thousands of cores. With the rise of multi-core architectures has come the need to teach advanced programmers a new and essential skill: how to program massively parallel processors.
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.
*Describes computational thinking techniques that will enable you to think about problems in ways that are amenable to high-performance parallel computing.
*Utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments.
*Shows you how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.
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| Customer Reviews:
Showing reviews 1-5 of 6
 great way to learn cuda February 12, 2010
S. Yutzy (Cleveland, OH)
9 out of 11 found this review helpful
One of the problems with many parallel programming books is that they take too general of an approach, which can leave the reader to figure out how to implement the ideas using the library of his/her choosing. There's certainly a place for such a book in the world, but not if you want to get up and running quickly.
Programming Massively Parallel Processors presents parallel programming from the perspective of someone programming an NVIDIA GPU using their CUDA platform. From matrix multiplication (the "hello world" of the parallel computing world) to fine-tuned optimization, this book walks the reader through step by step not only how to do it, but how to think about it for any arbitrary problem.
The introduction mentions that this book does not require a background in computer architecture or C/C++ programming experience, and while that's largely true, I think it would be extremely helpful to come into a topic like this with at least some exposure in those areas.
Summary: this book is the best reference I've found for learning parallel programming "the CUDA way". Many of the concepts will carry over to other approaches (OpenMP, MPI, etc.), but this is by and large a CUDA book. Highly recommended.
 Effective for beginners, good intro to CUDA and Tesla for pros February 25, 2010
John West
4 out of 4 found this review helpful
As a beginning text this book has a significant advantage that beginning texts written for MPI, OpenMP, and so on don't have: there are 200 million CUDA-capable GPUs already deployed, and the odds are pretty good that most readers either have, or can readily get access to, a computer on which they can meaningfully learn parallel programming. If you are new to parallel programming and have access to a Tesla GPU, this book is a fine place to start your education. Readers already comfortable with parallel programming will find clear explanations of the Tesla GPU architecture and the performance implications of its hardware features, as well as a solid introduction to the principles of programming in CUDA, though they'll probably do a lot of skimming over the already-familiar basics.
Great for beginners February 22, 2010
Raymond Tay (singapore)
3 out of 3 found this review helpful
I think this book was written with the beginner in mind - if you're new to CUDA and having issues with understanding NVIDIA's documentation on the subject then this is the book to get. The author(s) took time to clarify and solidify some of the more difficult terms to understand e.g. memory bandwidth utilization, optimizing strategies but there are shortcomings in the book and two i could think of are typos (this really an issue cos it happens to every other book i've read) and the other would be using more examples to solidify concepts and illustrating them.
In a nutshell, a great beginner's book but not a handbook sort of book.
 A fine introductory text February 22, 2010
Lars Bergstrom (Chicago, IL)
3 out of 3 found this review helpful
This book fills a nice gap between the SDK samples, technical specifications, and online course content. If you are just getting started with GPGPU computing, this book leads you smoothly through the computation model, hardware architecture, and the programming model required to take advantage of the hardware.
As others have pointed out, this is not a large book and fairly expensive. But, for the first book on the market it's surprisingly useful, effective, and readable. Definitely recommended for newcomers to the platform. Experienced GPGPU developers should only pick it up as a "hand out" for the people you need to train up, though.
OK as a beginner's book February 18, 2010
D. Good (Redmond, WA USA)
2 out of 4 found this review helpful
If you haven't done much low-level programming, and you plan to use the NVIDIA CUDA architecture, this book will help you get started. The pace is slow. Things like indexing into multi-dimensional spaces are explained in excruciating detail. However, the author does a good job of breaking down the levels of parallelism that the CUDA architecture can provide.
There's quite a bit of info online from the GPU conference last fall that will take you farther.
Showing reviews 1-5 of 6
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