Programming massively parallel processors a hands-on approach

Verlag Elsevier Reference Monographs, Kopierschutz DRM.

In addition to explaining the language and the architecture, they define the nature of data parallel problems that run well on the heterogeneous CPU-GPU hardware This book is a valuable addition to the recently reinvigorated parallel computing literature. The hands-on learning included is cutting-edge, yet very readable. This is a most rewarding read for students, engineers, and scientists interested in supercharging computational resources to solve today's and tomorrow's hardest problems. They have done it again in this book. This joint venture of a passionate teacher and a GPU evangelizer tackles the trade-off between the simple explanation of the concepts and the in-depth analysis of the programming techniques. This is a great book to learn both massive parallel programming and CUDA.

Programming massively parallel processors a hands-on approach

Unlike normal programming books, it talks a lot about how GPUs work and how the introduced techniques fit in that picture. Strongly recommended. I bought the first edition when it came out, and definitely it was a gold mine of information on the subject. I wonder though, is the fourth edition worth buying another copy? But none of that was present when this book came out in It would be great if the authors revisited all the early chapters to modernize that content, but that's a lot of work so I don't usually count on authors making such an effort for later editions. I also read the older edition and got the 4th for the second read recently. I felt that the updated coverage is more on the GPU side than the language side. It covers new GPU features and architectures well. I don't think it covers Tensor core things. But I might be wrong. Ah thanks! That's good to know. AlexDenisov 7 months ago prev next [—]. I have the book but didn't know about these, thanks for the link!

This is a great book to learn both massive parallel programming and CUDA. Application case study—non-Cartesian magnetic resonance imaging: An introduction to statistical estimation methods Abstract Ah thanks!

Wen mei W. Hwu , David B. 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. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. For this new edition, the authors are updating their coverage of CUDA, including the concept of unified memory, and expanding content in areas such as threads, while still retaining its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses.

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. David B. Kirk is well recognized for his contributions to graphics hardware and algorithm research. By the time he began his studies at Caltech, he had already earned B. At NVIDIA, Kirk led graphics-technology development for some of today's most popular consumer-entertainment platforms, playing a key role in providing mass-market graphics capabilities previously available only on workstations costing hundreds of thousands of dollars. Kirk holds 50 patents and patent applications relating to graphics design and has published more than 50 articles on graphics technology, won several best-paper awards, and edited the book Graphics Gems III. A technological "evangelist" who cares deeply about education, he has supported new curriculum initiatives at Caltech and has been a frequent university lecturer and conference keynote speaker worldwide.

Programming massively parallel processors a hands-on approach

Programming Massively Parallel Processors: A Hands-on Approach, Third Edition shows both student and professional alike the basic concepts of parallel programming and GPU architecture, exploring, in detail, various techniques for constructing parallel programs. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in-depth. For this new edition, the authors have updated their coverage of CUDA, including coverage of newer libraries, such as CuDNN, moved content that has become less important to appendices, added two new chapters on parallel patterns, and updated case studies to reflect current industry practices. Kirk, Wen-mei W. Cooper, Linda Torczon. This entirely revised second edition of Engineering a Compiler is full of technical updates and new …. Skip to main content. There are also live events, courses curated by job role, and more.

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There is now a great need for software developers to learn about parallel programming, which is the focus of this book. Neuheiten Bestseller Firmenlizenz. Verlag Elsevier Reference Monographs, Mediengruppe Stein. The multicore trajectory seeks to maintain the execution speed of sequential programs while moving into multiple cores. This is a most rewarding read for students, engineers, and scientists interested in supercharging computational resources to solve today's and tomorrow's hardest problems. Memory and data locality Abstract 4. In addition to explaining the language and the architecture, they define the nature of data parallel problems that run well on the heterogeneous CPU-GPU hardware The hardware takes advantage of the large number of threads to find work to do when some of them are waiting for long-latency memory accesses or arithmetic operations. This joint venture of a passionate teacher and a GPU evangelizer tackles the trade-off between the simple explanation of the concepts and the in-depth analysis of the programming techniques. The many-threads began with a large number of threads, and once again, the number of threads increases with each generation. Skaffa ett abonnemang. Bokrea start.

Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses.

I also read the older edition and got the 4th for the second read recently. Kopierschutz DRM. He is the director of the OpenIMPACT project, which has delivered new compiler and computer architecture technologies to the computer industry since Historically, most software developers have relied on the advances in hardware to increase the speed of their sequential applications under the hood; the same software simply runs faster as each new generation of processors is introduced. These are not necessarily application speeds, but are merely the raw speed that the execution resources can potentially support in these chips: 1. I have the book but didn't know about these, thanks for the link! But none of that was present when this book came out in Parallel patterns: sparse matrix computation: An introduction to data compression and regularization Abstract Parallel patterns: prefix sum: An introduction to work efficiency in parallel algorithms Abstract 8. AU - Kirk, David B. Get it now. The many-threads began with a large number of threads, and once again, the number of threads increases with each generation. That's good to know.