Cuda Programming A Developers Guide To Parallel Computing With Gpus - Info and Reading Options
By Shane Cook
"Cuda Programming A Developers Guide To Parallel Computing With Gpus" was published by Morgan Kaufmann Publishers in 2012 - Amsterdam Boston and it has 592 pages.
“Cuda Programming A Developers Guide To Parallel Computing With Gpus” Metadata:
- Title: ➤ Cuda Programming A Developers Guide To Parallel Computing With Gpus
- Author: Shane Cook
- Number of Pages: 592
- Publisher: Morgan Kaufmann Publishers
- Publish Date: 2012
- Publish Location: Amsterdam Boston
“Cuda Programming A Developers Guide To Parallel Computing With Gpus” Subjects and Themes:
- Subjects: ➤ Application software, development - Computer architecture - Parallel programming (computer science) - Application software - Development - Parallel processing (Electronic computers) - Distributed systems & computing - Parallel - General - Professional, career & trade -> computer science -> programming languages (jr/sr) - Professional, career & trade -> engineering -> software engineering - Professional, career & trade -> computer science -> system administration - Graphics processing units
Edition Identifiers:
- The Open Library ID: OL26079075M - OL17492053W
- Online Computer Library Center (OCLC) ID: 842439171
- Library of Congress Control Number (LCCN): 2013371002
- ISBN-13: 9780124159334
- All ISBNs: 9780124159334
AI-generated Review of “Cuda Programming A Developers Guide To Parallel Computing With Gpus”:
"Cuda Programming A Developers Guide To Parallel Computing With Gpus" Description:
Open Data:
"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."
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