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"Parallel programming is about performance, for otherwise you’d write a sequential program. For those interested in learning or teaching the topic, a problem is where to find truly parallel hardware that can be dedicated to the task, for it is difficult to see interesting speedups if its shared or only modestly parallel. One answer is graphical processing units (GPUs), which can have hundreds of cores and are found in millions of desktop and laptop computers. For those interested in the GPU path to parallel enlightenment, this new book from David Kirk and Wen-mei Hwu is a godsend, as it introduces CUDA, a C-like data parallel language, and Tesla, the architecture of the current generation of NVIDIA GPUs. In addition to explaining the language and the architecture, they define the nature of data parallel problems that run well on heterogeneous CPU-GPU hardware. More concretely, two detailed case studies demonstrate speedups over CPU-only C programs of 10X to 15X for naïve CUDA code and 45X to 105X for expertly tuned versions. They conclude with a glimpse of the future by describing the next generation of data parallel languages and architectures: OpenCL and the NVIDIA Fermi GPU. This book is a valuable addition to the recently reinvigorated parallel computing literature."
David Patterson
Director, The Parallel Computing Research Laboratory
Pardee Professor of Computer Science, U.C. Berkeley
Co-author of Computer Architecture: A Quantitative Approach
"Written by two teaching pioneers, this book is the definitive practical reference on programming massively parallel processors—a true technological gold mine. The hands-on learning included is cutting-edge, yet very readable. This is a most rewarding read for students, engineers and scientists interested in supercharging computational resources to solve today's and tomorrow's hardest problems."
Nicolas Pinto
MIT, NVIDIA Fellow 2009
"The use of GPUs is having a big impact in scientific computing. David Kirk and Wen-mei Hwu's new book is an important contribution towards educating our students on the ideas and techniques of programming for massively-parallel processors."
Mike Giles
Professor of Scientific Computing
University of Oxford
"This book is the most comprehensive and authoritative introduction to GPU computing yet. David Kirk and Wen-mei Hwu are the pioneers in this increasingly important field, and their insights are invaluable and fascinating. This book will be the standard reference for years to come."
Hanspeter Pfister
Harvard University
"This is a vital and much needed text. GPU programming is growing by leaps and bounds. Having a coherent text vs. slides and online course materials that are spread out makes a course not only more organized, but actually more likely to even happen at all. This topic coverage will be very welcomed and highly useful across interdisciplinary fields."
Shannon Steinfadt
Kent State University
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