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An efficient optimization technique for task matching and scheduling in heterogeneous computing systems

机译:异构计算系统任务匹配与调度的有效优化技术

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A new optimization technique, the Genetic Annealing Algorithm (GAA), is proposed in this paper 10 solve the task matching and scheduling problem in a heterogeneous computing system. The GAA is simple in design; it employs only the stir operation, a novel idea with the annealing concept, to locate optimal solutions. Experimental evaluation shows that compared with the Genetic Algorithm, Simulated Annealing and Guided Evolutionary Simulated Annealing approaches, the GAA yields constantly favorable performance in terms of speedup, running time, cost and complexity.
机译:本文提出了一种新的优化技术,遗传退火算法(GaA),在本文中提出了在异构计算系统中解决任务匹配和调度问题。 Gaa的设计简单;它只使用搅拌操作,与退火概念的新颖思想,定位最佳解决方案。实验评估表明,与遗传算法相比,模拟退火和引导的进化模拟退火方法,GAA在加速,运行时间,成本和复杂性方面不断有利。

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