An Automatic and Symbolic Parallelization System for Distributed Memory Parallel Computers
K. Ikudome, Geoffrey Fox, Adam Kolawa, Jon W. Flower · 2005
This paper describes ASPAR (Automatic and Symbolic PARallelization) which consists of a source-to-source parallelizer and a set of interactive graphic tools. While the issues of data dependency have already been explored and used in many parallel computer systems such as vector and shared memory machines, distributed memory parallel computers require, in addition, explicit data decomposition. New symbolic analysis and data-dependency analysis methods are used to determine an explicit data decomposition scheme. Automatic parallelization models using high level communications are also described in this paper. The target applications are of the “regular-mesh" type typical of many scientific calculations. The system has been implemented for the language C, and is designed for easy modification for other languages such as Fortran.