Parallelizing of sequential annotated programs in PVM environment

Abstract

In this paper an approach to dynamic parallelizing of coarse and medium grained program is proposed where the parallelization sources are both dataflow analysis and the features given in the program by annotating some of their operators. Program annotation enables to support two additional types of parallel computations which cannot be found out only from the analysis of dataflow dependencies. First, there are the speculative computations based on anticipating alternative branches of the program's computational process. Second, there are pipeline computations that sometimes may be initialized for operators at the moment when their input data are not complete. The system for dynamic parallelizing of programs is implemented in C++/PVM for PC clusters, and experiments from Buchberger's algorithm are presented.