Programming Massively Parallel Processors (e-bog) af Hwu, Wen-mei W.
Hwu, Wen-mei W. (forfatter)

Programming Massively Parallel Processors e-bog

25,00 DKK (inkl. moms 31,25 DKK)
Programming Massively Parallel Processors discusses 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. This book describes computational thinking techniques...
E-bog 25,00 DKK
Forfattere Hwu, Wen-mei W. (forfatter)
Udgivet 22 februar 2010
Længde 280 sider
Genrer Computer programming / software engineering
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9780123814739
Programming Massively Parallel Processors discusses 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. This book describes computational thinking techniques that will enable students to think about problems in ways that are amenable to high-performance parallel computing. It utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments. Studies learn how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL. This book is recommended for advanced students, software engineers, programmers, and hardware engineers. 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.