CUDA Programming: A Developer's Guide to Parallel Computing with GPUs (Applications of Gpu Computing) - Tapa blanda

"I must mention chapters 7, which deals with the practicalities of using the SDK, and 9, which offers advice and a detailed breakdown of areas that can limit the performance of a CUDA application. Together, these chapters transform this good book into the kind of excellent text that all CUDA developers can find useful, regardless of their relative experience."--ComputingReviews.com, July 12, 2013 "This book is one of the most comprehensive on the subject published to date...it will guide those acquainted with GPU/CUDA from other books or from NVIDIA product documentation through the optimization maze to efficient CUDA/GPU coding."--ComputingReviews.com, April 25, 2013

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems.

• Comprehensive introduction to parallel programming with CUDA, for readers new to both
• Detailed instructions help readers optimize the CUDA software development kit
• Practical techniques illustrate working with memory, threads, algorithms, resources, and more
• Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets
• Each chapter includes exercises to test reader knowledge