Programming massively parallel processors a hands-on approach

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.

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

Programming massively parallel processors a hands-on approach

Verlag Elsevier Reference Monographs, Kopierschutz DRM. Chapter 1 Introduction Chapter Outline 1. Microprocessors based on a single central processing unit CPU , such as those in the Intel Pentium family and the AMD Opteron family, drove rapid performance increases and cost reductions in computer applications for more than two decades. This relentless drive for performance improvement has allowed application software to provide more functionality, have better user interfaces, and generate more useful results. The users, in turn, demand even more improvements once they become accustomed to these improvements, creating a positive virtuous cycle for the computer industry. This drive, however, has slowed since due to energy consumption and heat dissipation issues that limited the increase of the clock frequency and the level of productive activities that can be performed in each clock period within a single CPU. Since then, virtually all microprocessor vendors have switched to models where multiple processing units, referred to as processor cores, are used in each chip to increase the processing power. This switch has exerted a tremendous impact on the software developer community [Sutter]. Traditionally, the vast majority of software applications are written as sequential programs, as described by von Neumann in his seminal report in [vonNeumann]. The execution of these programs can be understood by a human sequentially stepping through the code. 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. Computer users have also become accustomed to the expectation that these programs run faster with each new generation of microprocessors. Such expectation is no longer valid from this day onward. A sequential program will only run on one of the processor cores, which will not become significantly faster than those in use today.

Skip to main content. The users, in turn, demand even more improvements once they become accustomed to these improvements, creating a positive virtuous cycle for the computer industry. Case studies demonstrate the development process, detailing computational thinking and ending with effective and efficient parallel programs.

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. Kirk, Wen-mei W. Cooper, Linda Torczon. This entirely revised second edition of Engineering a Compiler is full of technical updates and new ….

Programming massively parallel processors a hands-on approach

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. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. New chapters on frequently used parallel patterns have been added, and case studies have been updated to reflect current industry practices. Wen-mei W. His research interests are in the area of architecture, implementation, compilation, and algorithms for parallel computing. Hwu received his Ph. David B.

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Together they form a unique fingerprint. Parallel patterns: sparse matrix computation: An introduction to data compression and regularization Abstract Traditionally, the vast majority of software applications are written as sequential programs, as described by von Neumann in his seminal report in [vonNeumann]. I have the book but didn't know about these, thanks for the link! The answer lies in the differences in the fundamental design philosophies between the two types of processors, as illustrated in Figure 1. This new, dramatically escalated incentive for parallel program development has been referred to as the concurrency revolution [Sutter]. 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. Conclusion and outlook Abstract Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. I wonder though, is the fourth edition worth buying another copy? Navigation Navigation.

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.

Figure 1. Logga in. AlexDenisov 7 months ago prev next [—]. The prevailing solution is to optimize for the execution throughput of massive numbers of threads. AU - Kirk, David B. It makes use of sophisticated control logic to allow instructions from a single thread to execute in parallel or even out of their sequential order while maintaining the appearance of sequential execution. I wonder though, is the fourth edition worth buying another copy? Verlag Elsevier Reference Monographs, Ladda ned. All rights reserved.