Performance Evaluation of List Based Scheduling on Heterogeneous Systems
This paper addresses the problem of evaluating the schedules produced by list based scheduling algorithms, with metaheuristic algorithms. Task scheduling in heterogeneous systems is a NP-problem, therefore several heuristic approaches were proposed to solve it. These heuristics are categorized into several classes, such as list based, clustering and task duplication scheduling. Here we consider the list scheduling approach. The objective of this study is to assess the solutions obtained by list based algorithms to verify the space of improvement that new heuristics can have considering the solutions obtained with metaheuritcs that are higher time complexity approaches. We concluded that for a low Communication to Computation Ratio (CCR) of 0.1, the schedules given by the list scheduling approach is in average close to metaheuristic solutions. And for CCRs up to 1 the solutions are below 11% worse than the metaheuristic solutions, showing that it may not be worth to use higher complexity approaches and that the space to improve is narrow.
KeywordsSchedule Algorithm Tabu Search Direct Acyclic Graph Task Graph Metaheuristic Algorithm
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