By the author of the classic 1989 monograph, Optimizing Supercompilers for Supercomputers, this book covers the knowledge and skills necessary to build a competitive, advanced compiler for parallel or high-performance computers. Starting with a review of basic terms and algorithms used-such as graphs, trees, and matrix algebra-Wolfe shares the lessons of his 20 years experience developing compiler products such as KAP, the capstone product of Kuck and Associates, Inc., of Champaign, Illinois.
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From the Back Cover
High Performance Compilers for Parallel Computing provides a clear understanding of the analysis and optimization methods used in modern commercial research compilers for parallel systems. By the author of the classic 1989 monograph Optimizing Supercompilers for Supercomputers, this book covers the knowledge and skills necessary to build a competitive, advanced compiler for parallel or high-performance computers. Starting with a review of basic terms and algorithms used - such as graphs, trees, and matrix algebra - Wolfe shares the lessons of his 20 years experience developing compiler products. He provides a complete catalog of program restructuring methods that have proven useful in the discovery of parallelism or performance optimization and discusses compiling details for each type of parallel system described, from simple code generation, through basic and aggressive optimizations. A wide variety of parallel systems are presented, from bus-based cache-coherent shared memory multiprocessors and vector computers, to message-passing multicomputers and large-scale shared memory systems.
0805327304B04062001
About the Author
As co-founder in 1979 of Kuck and Associates, Inc., Michael Wolfe helped develop KAP restructuring, parallelizing compiler software. In 1988, Wolfe joined the Oregon Graduate Institute of Science and Technology faculty, directing research on language and compiler issues for high performance computer systems. His current research includes development and implementation of program restructuring transformations to optimize programs for execution on parallel computers, refinement and application of recent results in analysis techniques to low level compiler optimizations, and analysis of data dependence decision algorithms.
0805327304AB04062001
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10 of 10 people found the following review helpful:
5.0 out of 5 stars
Essential reference for compiler writers,
By wiredweird "wiredweird" (Earth, or somewhere nearby) - See all my reviews (HALL OF FAME REVIEWER) (TOP 500 REVIEWER)
This review is from: High-Performance Compilers for Parallel Computing (Paperback)
This is a modern classic. If you develop compilers for high performance computing (HPC), this must be on your shelves. It has a heavy emphasis on Fortran, the workhorse of HPC, but is widely applicable to other languages as well. The majority of the book's content reflects the large majority of processors that carry today's HPC load: sequential, von Neumann engines, even the computing ensemble as a whole has lots of them.
This book's real contribution is in its analysis of the loops that process arrays. Wolfe presents a number of ways to characterize dependencies, using quantitive techniques that go well beyond the graph-based presentations elsewhere. By casting the dependency problem in terms of integer programming or linear algebra, Wolfe make huge bodies of problem-solving knowledge available to the compiler developer. He also uses these quantitative terms to give new insight into loop transformations that the reader may already understand. Despite the irreplaceable value of this book, I found it maddening to read. For some reason, the periods dropped off of nearly every sentence in the text. Then, just when I got used to that quirk, the periods appeared again. Their coming and going was so irregular throughout the book that I never really got into a steady reading rhythm. A much worse problem appeared throughout the first chapter, though. It's an exceptional discussion of matrix multiplication, a staple of performance computing. The chapter presents it again and again, to demonstrate differences in looping constructs and the organization of memory access. That part of the discussion was great. The problem is that it's wrong - a systematic error, in seemingly every example, replaced the scalar multiplication at the core of the algorithm with addition. It's hard enough trying to understand the interactions of loops nested five deep, language features, and memory hierarchies. Doing all that while mentally correcting the text's blunders is simply infuriating. Perhaps those problems were fixed after the 1996 edition that I read - for the reader's sake, I hope so. As it was, that first chapter left me wary of everything else in the book. If you need it, though, you need it. Grit your teeth, brace yourself, and dive in. This is a valuable complement to the Allen&Kennedy text, and essential for anyone creating compilers for HPC architectures. //wiredweird
2 of 3 people found the following review helpful:
4.0 out of 5 stars
A Practitioners Guide,
By A Student (USA) - See all my reviews
This review is from: High-Performance Compilers for Parallel Computing (Paperback)
This book covers a lot of ground. Wolfe starts off with a chapter on machine architecture, then moves into language features that can be parallelized. Then there are chapters on graphs and linear algebra then he dives into an encyclopedia of data dependence, data flow, and control flow algorithms. I only made it about 1/3 of the way thru the book as it is oriented toward people actually implementing high performance compilers ie it's a practitioners guide. I gave the book four stars because the type setting (previously mentioned lack of periods) is appalling. Especially in this day and age.
2 of 3 people found the following review helpful:
5.0 out of 5 stars
It's the de-facto bible for parallel compiler optimizations,
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This review is from: High-Performance Compilers for Parallel Computing (Paperback)
If you want to get into data dependency analysis of compilers, this book is absolutely the best. Many compiler book authors do not have the experience of writing a compiler of industrial strength, but Michael Wolfe does.
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