Table of Contents Author Guidelines Submit a Manuscript
Scientific Programming
Volume 6, Issue 1, Pages 3-27
http://dx.doi.org/10.1155/1997/195689

A Linear Algebra Framework for Static High Performance Fortran Code Distribution

Corinne Ancourt, Fabien Coelho, FranÇois Irigoin, and Ronan Keryell

Centre de Recherche en Informatique, École Nationale Supérieure des Mines de Paris, 35, rue Saint-Honoré, F-77305 Fontainebleau cedex, France

Received 26 May 1995; Accepted 26 November 1995

Copyright © 1997 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

High Performance Fortran (HPF) was developed to support data parallel programming for single-instruction multiple-data (SIMD) and multiple-instruction multiple-data (MIMD) machines with distributed memory. The programmer is provided a familiar uniform logical address space and specifies the data distribution by directives. The compiler then exploits these directives to allocate arrays in the local memories, to assign computations to elementary processors, and to migrate data between processors when required. We show here that linear algebra is a powerful framework to encode HPF directives and to synthesize distributed code with space-efficient array allocation, tight loop bounds, and vectorized communications for INDEPENDENT loops. The generated code includes traditional optimizations such as guard elimination, message vectorization and aggregation, and overlap analysis. The systematic use of an affine framework makes it possible to prove the compilation scheme correct.