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Programming Massively Parallel Processors: A Hands-on Approach |  | Authors: David B. Kirk, Wen-mei W. Hwu
Publisher: Morgan Kaufmann
List Price: $69.95
Buy New: $47.48
as of 7/30/2010 10:36 CDT details
You Save: $22.47 (32%)
New (31) Used (9) from $46.52
Seller: s_r_books
Rating:  8 reviews
Sales Rank: 9698
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.
- Teaches computational thinking and problem-solving techniques that facilitate 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 8
 Great introduction to CUDA May 23, 2010
Husam Abu-Haimed (California, USA)
0 out of 1 found this review helpful
A great introduction to programming GPUs using CUDA. The writing is concise and easy to read and understand. Most programmer should be able to read this book in a couple of days.
a little odd but good enough for first pass March 20, 2010
Sergei Morozov (Stanford, CA United States)
10 out of 10 found this review helpful
This book is a much better introduction to programming GPUs via CUDA than CUDA manual, or some presentation floating on the web. It is a little odd in coverage and language. You can tell it is written by two people with different command of English as well as passion. One co-author seems to be trying very hard to be colorful and looking for idiot-proof analogies but is prone to repetition. The other co-author sounds like a dry marketing droid sometimes. There are some mistakes in the codes in the book, but not too many since they don't dwell too long on code listings. In terms of coverage, I wish they'd cover texture memories, profiling tools, examples beyond simple matrix multiplication, and advice on computational thinking for codes with random access patterns. Chapters 6, 8, 9, and 10 are worth reading several times as they are full of practical tricks to use to trade one performance limiter for another in the quest for higher performance.
Effective for beginners, good intro to CUDA and Tesla for pros February 25, 2010
John West
6 out of 7 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.
 A fine introductory text February 22, 2010
Lars Bergstrom (Chicago, IL)
8 out of 9 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.
Great for beginners February 22, 2010
Raymond Tay (singapore)
8 out of 8 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.
Showing reviews 1-5 of 8
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