Abstract

We present a low complexity heuristic named the Dominant Sequence Clustering algorithm (DSC) for scheduling parallel tasks on an unbounded number of completely connected processors. The performance of DSC is comparable or even better on average than many other higher complexity algorithms. We assume no task duplication and nonzero communication overhead between processors. Finding the optimum solution for arbitrary directed acyclic task graphs (DAGs) is NP-complete. DSC finds optimal schedules for special classes of DAGs such as fork, join, coarse grain trees and some fine grain trees. It guarantees a performance within a factor of two of the optimum for general coarse grain DAGs. We compare DSC with three higher complexity general scheduling algorithms, the MD by Wu and Gajski [19], the ETF by Hwang, Chow, Anger and Lee [12] and Sarkar's clustering algorithm [17]. We also give a sample of important practical applications where DSC has been found useful. Index Terms -- Clustering, dire...

Citations