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Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)

Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)

Last update 9 months ago

262.50 EGP

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Last update 9 months ago

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 (Graphic...

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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 (Graphic...

Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series) Details

  • The best price of Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series) by CAIRO BOOKS in Egypt is 262.50 EGP
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  • The first appearance of this product was on Aug 20, 2014

CAIRO BOOKS's Description

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. Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing. Utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments. Shows you how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.

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