Professional Cuda C Programming - by John Cheng & Max Grossman & Ty McKercher (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><b>Break into the powerful world of parallel GPU programming </b><b>with this down-to-earth, practical guide</b></p> <p>Designed for professionals across multiple industrial sectors, <i>Professional CUDA C Programming </i>presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the hard and soft aspects of GPU programming.</p> <p>Computing architectures are experiencing a fundamental shift toward scalable parallel computing motivated by application requirements in industry and science. This book demonstrates the challenges of efficiently utilizing compute resources at peak performance, presents modern techniques for tackling these challenges, while increasing accessibility for professionals who are not necessarily parallel programming experts. The CUDA programming model and tools empower developers to write high-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive programming experience. Recognized CUDA authorities John Cheng, Max Grossman, and Ty McKercher guide readers through essential GPU programming skills and best practices in <i>Professional CUDA C Programming</i>, including: </p> <ul> <li>CUDA Programming Model</li> <li>GPU Execution Model</li> <li>GPU Memory model</li> <li>Streams, Event and Concurrency</li> <li>Multi-GPU Programming</li> <li>CUDA Domain-Specific Libraries</li> <li>Profiling and Performance Tuning</li> </ul> <p>The book makes complex CUDA concepts easy to understand for anyone with knowledge of basic software development with exercises designed to be both readable and high-performance. For the professional seeking entrance to parallel computing and the high-performance computing community, <i>Professional CUDA C Programming</i> is an invaluable resource, with the most current information available on the market.</p><p/><br></br><p><b> From the Back Cover </b></p></br></br><p><b>Break into the powerful world of parallel computing</b> <p>Focused on the essential aspects of CUDA, <i>Professional CUDA C Programming</i> offers down-to-earth coverage of parallel computing. Packed with examples and exercises that help you see code, real-world applications, and try out new skills, this resource makes the complex concepts of parallel computing accessible and easy to understand. Each chapter is organized around one central topic, and includes workable examples that demonstrate the development process, allowing you to measure significant performance gains while exploring all aspects of GPU programming. <p><i>Professional CUDA C Programming: </i> <ul> <li> Focuses on GPU programming skills and best practices that deliver outstanding performance</li> <li> Shows you how to think in parallel</li> <li> Turns complex subjects into easy-to-understand concepts</li> <li> Makes information accessible across multiple industrial sectors</li> <li> Features helpful examples and exercises in each chapter</li> <li> Covers the essentials for those who are not experts in C programming</li> </ul> <p><b>wrox.com</b> <p><b>Programmer Forums</b> <p>Join our Programmer to Programmer forums to ask and answer programming questions about this book, join discussions on the hottest topics in the industry, and connect with fellow programmers from around the world. <p><b>Code Downloads</b> <p>Take advantage of free code samples from this book, as well as code samples from hundreds of other books, all ready to use. <p><b>Read More</b> <p>Find articles, e-books, sample chapters, and tables of contents for hundreds of books, and more reference resources on programming topics that matter to you.<p/><br></br><p><b> About the Author </b></p></br></br><p><b>John Cheng, PHD, </b> is a Research Scientist at BGP International in Houston. He has developed seismic imaging products with GPU technology and many high-performance parallel production applications on heterogeneous computing-platforms. <p><b>Max Grossman</b> is an expert in GPU computing with experience applying CUDA to problems in medical imaging, machine learning, geophysics, and more. <p><b>Ty McKercher</b> has been helping customers adopt GPU acceleration technologies while he has been employed at NVIDIA since 2008.
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