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| Author(s): | Jason Sanders Edward Kandrot | | Published: | 28 Jul 2010
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Written by two senior members of the CUDA software platform team, this book shows programmers how to employ each area of CUDA through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You will discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.
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| Author(s): | Rob Farber | | Published: | 14 Nov 2011
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As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA Application Design and Development starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achieving high performance, maintaining competitiveness, analyzing CUDA benefits versus costs, and determining application lifespan Written by Rob Farber, author of the popular "Super Computing for the Masses" series in Dr Dobbs Journal.
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| Author(s): | Wen-Mei Hwu | | Published: | 12 Oct 2011
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This is the second volume of Morgan Kaufmanns GPU Computing Gems, offering an all-new set of insights, ideas, and practical, hands-on, skills from researchers and developers worldwide. Each chapter gives you a window into the work being performed across a variety of application domains, and the opportunity to witness the impact of parallel GPU computing on the efficiency of scientific research.
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| Author(s): | Wen-Mei Hwu | | Published: | 7 Apr 2011
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GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's Applications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, and video / image processing
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| Author(s): | Wen-Mei Hwu David Kirk | | Published: | 5 Feb 2010
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Multi-core processors are no longer the future of computing-they are the present day reality. A typical mass-produced CPU features multiple processor cores, while a GPU (Graphics Processing Unit) may have hundreds or even thousands of cores. With the rise of multi-core architectures has come the need to teach advanced programmers a new and essential skill: how to program massively parallel processors.
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