Abstract
Task partitioning is an important technique in parallel processing. In this paper, we investigate the optimal partitioning strategies and granularities of tasks with communications based on several models of parallel computer systems. Different from the usual approach, we study the optimal partitioning strategies and granularities from the viewpoint of minimizingT as well as minimizingNT 2, whereN is the number of processors used andT is the program execution time usingN processors. Our results show that the optimal partitioning strategies for all cases discussed in this paper are the same—either to assign all tasks to one processor or to distribute them among the processors as equally as possible depending only on the functions of ratio of running time to communication timeR/C.
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