Coarse-Grain Parallel Programming in Jade

Abstract

This paper presents Jade, a language which allows a programmer to easily express dynamic coarse-grain parallelism. Starting with a sequential program, a programmer augments those sections of code to be parallelized with abstract data usage information. The compiler and run-time system use this information to concurrently execute the program while respecting the progmm�s data dependence constraints. Using Jade can significantly reduce the time and effort required to develop and maintain a parallel version of an imperative application with serial semantics. The paper introduces the basic principles of the language, compares Jade with other existing lrmguages, and presents the performance of a sparse matrix Cholesky factorization algorithm implemented in Jade. © 1991, ACM. All rights reserved.