Task Scheduling using Parallel Genetic Algorithm implemented with GRADE

In this paper, we present a task scheduling heuristic, based on a parallel genet ic algorithm (PGA). The algorithm schedules parallel programs, represented as directed acyclic graphs (DAGs), onto multi-processor systems with dy namic interconnection networks (DIN). It combines PGA with list scheduling approach and takes into account inter-processor communication cost, link contention in the DIN and changes of inter-processor connections. Parallel Genetic Algori thm is currently implemented on a cluster of workstations in GRADE environment.

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