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GPU Computing Gems (Emerald Edition)



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Author: Wen-mei W. Hwu

Publisher: Morgan Kaufmann

Genres:

Publish Date: February 7, 2011

ISBN-10: 123849888

Pages: 886

File Type: PDF

Language: English

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Book Preface

We are entering the golden age of GPU computing. Since the introduction of CUDA in 2007, more than 100 million computers with CUDA-capable GPUs have been shipped to end users. Unlike the previous GPGPU shader programming models, CUDA supports parallel programming in C. From my own experience in teaching CUDA programming, C programmers can begin to write basic CUDA programs after only attending one lecture and reading one textbook chapter. With such a low barrier of entry, researchers all over the world have been engaged in developing new algorithms and applications to take advantage of the extreme floating point execution throughout these GPUs.

Today, there is a large community of GPU computing practitioners. Many of them have reported a 10 to 100 times speedup of their applications with GPU computing. To put this into perspective, with the historical 2X performance growth every 2 years, these researchers are experiencing the equivalent of time travel of 8 to 12 years. That is, they are getting the performance today that they would have to wait for 8 to 12 years if they went for the “free-ride” advancement of performance in microprocessors. Interestingly, such “free ride” advancement is no longer available. Furthermore, once they develop their application in CUDA, they will likely see continued performance growth of 2X for every two years from this day forward. After discussing with numerous researchers, I have reached the conclusion that many of them are solving similar algorithm problems in their programming efforts. Although they are working on diverse applications, they often end up developing similar algorithmic strategies. The idea of GPU Computing Gems is to provide a convenient means for application developers in diverse application areas to benefit from each other’s experience. In this volume, we have collected 50 gem articles written by researchers in 10 diverse areas. Each gems article reports a successful application experience in GPU computing. These articles describe the techniques or “secret sauce” that contributed to the success.

The authors highlight the potential applicability of their techniques to other application areas. In our ditorial process, we have emphasized the accessibility of these gems to researchers in other areas.


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