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Modern computer architectures designed with high-performance microprocessors offer tremendous potential gains in performance over previous designs. Yet their very complexity makes it increasingly difficult to produce efficient code and to realize their full potential. This landmark text from two leaders in the field focuses on the pivotal role that compilers can play in addressing this critical issue.
The basis for all the methods presented in this book is data dependence, a fundamental compiler analysis tool for optimizing programs on high-performance microprocessors and parallel architectures. It enables compiler designers to write compilers that automatically transform simple, sequential programs into forms that can exploit special features of these modern architectures.
The text provides a broad introduction to data dependence, to the many transformation strategies it supports, and to its applications to important optimization problems such as parallelization, compiler memory hierarchy management, and instruction scheduling. The authors demonstrate the importance and wide applicability of dependence-based compiler optimizations and give the compiler writer the basics needed to understand and implement them. They also offer cookbook explanations for transforming applications by hand to computational scientists and engineers who are driven to obtain the best possible performance of their complex applications.
The approaches presented are based on research conducted over the past two decades, emphasizing the strategies implemented in research prototypes at Rice University and in several associated commercial systems. Randy Allen and Ken Kennedy have provided an indispensable resource for researchers, practicing professionals, and graduate students engaged in designing and optimizing compilers for modern computer architectures.
* Offers a guide to the simple, practical algorithms and approaches that are most effective in real-world, high-performance microprocessor and parallel systems.
* Demonstrates each transformation in worked examples.
* Examines how two case study compilers implement the theories and practices described in each chapter.
* Presents the most complete treatment of memory hierarchy issues of any compiler text.
* Illustrates ordering relationships with dependence graphs throughout the book.
* Applies the techniques to a variety of languages, including Fortran 77, C, hardware definition languages, Fortran 90, and High Performance Fortran.
* Provides extensive references to the most sophisticated algorithms known in research.
Randy Allen and Ken Kennedy are famous for their contributions
to compiler design theory. This book is a clearly written
discussion of the issues involving loop optimization and
dependence analysis. While this book also covers scalar
optimization issues, it is naturally complemented by Steven
S. Muchnick's excellent book "Advanced Compiler Design and
Implementation".Randy Allen has spent many years implementing a variety of
compilers for supercomputers and hardware design languages.
While Ken Kennedy has published seminal theoretical work on
compiler optimization, he has also been involved in hands on
implementation as well. The experience of these two authors
results in a book which covers the huge body of knowledge in
compiler optimization and provides this knowledge in a
practical form that can be used by software engineers working
on compiler design.For anyone working on modern compilers that... read more
As a researcher in the field, this book was immediately useful to me. Nearly every source code transformation and optimization technique that I'm aware of is present in this book, which often saves sifting through stacks of papers or looking for an elusive reference. If you're looking for a book to teach you the basics of how compilers work, it certainly is not the appropriate place to begin, but if you already have one good book on that then this book will make an excellent companion to it. It was slightly annoying that the book comes with two loose pages, one errata list and another to tape over a page early in the book, but that's what you get with 1st editions. Overall it's very good and the errors are very minor typos as opposed to factual goofs.
This book is a very thorough look through all the ways you can extract and use parallelism and data dependencies advantageously in an optimized compiler, depending on your target architecture. As one example, this book contains every imaginable way to deal with arrays and loops and the maddeningly complex data dependancies that can result from their various interminglings. The book is refreshingly easy to read and contains pseudo-code and step-by-step examples everywhere you'd want to see them.
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| AVAILABILITY | |||
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