David Gelernter

David Padua

Utpal Banerjee

Alex Nicolau

This book contains papers selected for presentation at the Sixth Annual Workshop on Languages and Compilers for Parallel Computing. The workshop washosted by the Oregon Graduate Institute of Science and Technology. All the major research efforts in parallel languages and compilers are represented in this workshop series. The 36 papers in the volume aregrouped under nine headings: dynamic data structures, parallel languages, High Performance Fortran, loop transformation, logic and dataflow language implementations, fine grain parallelism, scalar analysis, parallelizing compilers, and analysis of parallel programs. The book represents a valuable snapshot of the state of research in the field in 1993.

6th International Workshop, Portland, Oregon, USA, August 12 - 14, 1993. Proceedings

Languages and Compilers for Parallel Computing

Automatic transformation of a sequential program into a parallel form is a subject that presents a great intellectual challenge and promises a great practical award. There is a tremendous investment in existing sequential programs, and scientists and engineers continue to write their application programs in sequential languages (primarily in Fortran). The demand for higher speedups increases. The job of a restructuring compiler is to discover the dependence structure and the characteristics of the given machine. Much attention has been focused on the Fortran do loop. This is where one expects to find major chunks of computation that need to be performed repeatedly for different values of the index variable. Many loop transformations have been designed over the years, and several of them can be found in any parallelizing compiler currently in use in industry or at a university research facility. The book series on KappaLoop Transformations for Restructuring Compilerskappa provides a rigorous theory of loop transformations and dependence analysis. We want to develop the transformations in a consistent mathematical framework using objects like directed graphs, matrices, and linear equations. Then, the algorithms that implement the transformations can be precisely described in terms of certain abstract mathematical algorithms. The first volume, Loop Transformations for Restructuring Compilers: The Foundations, provided the general mathematical background needed for loop transformations (including those basic mathematical algorithms), discussed data dependence, and introduced the major transformations. The current volume, Loop Parallelization, builds a detailed theory of iteration-level loop transformations based on the material developed in the previous book.

Loop Parallelization

G. Goos

J. Hartmanis

Jan Van Leeuwen

David Sehr

This book presents the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Languages and Compilers for Parallel Computing, LCPC'96, held in San Jose, California, in August 1996. The book contains 35 carefully revised full papers together with nine poster presentations. The papers are organized in topical sections on automatic data distribution and locality enhancement, program analysis, compiler algorithms for fine-grain parallelism, instruction scheduling and register allocation, parallelizing compilers, communication optimization, compiling HPF, and run-time control of parallelism.

LCPC'97

Dependence Analysis may be considered to be the second edition of the author's 1988 book, Dependence Analysis for Supercomputing. It is, however, a completely new work that subsumes the material of the 1988 publication. This book is the third volume in the series Loop Transformations for Restructuring Compilers. This series has been designed to provide a complete mathematical theory of transformations that can be used to automatically change a sequential program containing FORTRAN-like do loops into an equivalent parallel form. In Dependence Analysis, the author extends the model to a program consisting of do loops and assignment statements, where the loops need not be sequentially nested and are allowed to have arbitrary strides. In the context of such a program, the author studies, in detail, dependence between statements of the program caused by program variables that are elements of arrays. Dependence Analysis is directed toward graduate and undergraduate students, and professional writers of restructuring compilers. The prerequisite for the book consists of some knowledge of programming languages, and familiarity with calculus and graph theory. No knowledge of linear programming is required.

Utpal Banerjee

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