Professional CUDA C Programming

Break into the powerful world of parallel computing Focused on the essential aspects of CUDA, Professional CUDA C Programming 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. Professional CUDA C Programming: Focuses on GPU programming skills and best practices that deliver outstanding performance Shows you how to think in parallel Turns complex subjects into easy–to–understand concepts Makes information accessible across multiple industrial sectors Features helpful examples and exercises in each chapter Covers the essentials for those who are not experts in C programming Programmer Forums 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. Code Downloads Take advantage of free code samples from this book, as well as code samples from hundreds of other books, all ready to use. Read More 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.

John Cheng, P H D, 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. Max Grossman is an expert in GPU computing with experience applying CUDA to problems in medical imaging, machine learning, geophysics, and more. Ty McKercher has been helping customers adopt GPU acceleration technologies while he has been employed at NVIDIA since 2008.