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A Genetic Algorithm for Static Load Balancing in Parallel Heterogeneous Systems

机译:并行异构系统中静态负载均衡的遗传算法

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Parallel Processing refers to the concept of running tasks that can be run simultaneously on several processors. Load balancing and scheduling are very important and complex problems in multiprocessor systems. So that problems are NP-Complete problems. In this paper, we introduce a method based on genetic algorithms for scheduling and load balancing in parallel heterogeneous multi-processor systems. The results of the simulations indicate Genetic algorithm for scheduling and load balancing at in systems is better than LPT, SPT and FIFO. Simulations results indicate Genetic Algorithm reduces total response time and also it increase utilization.
机译:并行处理是指可以在多个处理器上同时运行的运行任务的概念。在多处理器系统中,负载平衡和调度是非常重要且复杂的问题。这样的问题就是NP完全问题。在本文中,我们介绍了一种基于遗传算法的并行异构多处理器系统中的调度和负载平衡方法。仿真结果表明,用于系统调度和负载均衡的遗传算法优于LPT,SPT和FIFO。仿真结果表明,遗传算法减少了总响应时间,并且提高了利用率。

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