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This paper presents a variant of simulated evolution technique for the static non-preemptive scheduling of parallel programs represented by directed acyclic graphs including inter-processor communication delays and contention onto a multiprocessor system with the dual objectives of reducing the total execution time and scaling with the number of processors. The premise of the authors' algorithm is Simulated Evolution, an effective optimization method based on the analogy with the natural selection process of biological evolution. The proposed technique, named Scheduling with Simulated Evolution (SES), combines simulated evolution with list scheduling, wherein simulated evolution efficiently determines suitable priorities which lead to a good solution by applying list scheduling as a decoding heuristic.
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