By
Randy Allen, CEO and President of Catalytic Compilers
Ken Kennedy, Rice University
Description
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.
