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首页> 外文期刊>Journal of Parallel and Distributed Computing >Data dependent loop scheduling based on genetic algorithms for distributed and shared memory systems
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Data dependent loop scheduling based on genetic algorithms for distributed and shared memory systems

机译：基于遗传算法的分布式共享存储系统数据依赖循环调度

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摘要

Many approaches have been described for the parallel loop scheduling problem for shared-memory systems, but little work has been done on the data-dependent loop scheduling problem (nested loops with loop carried dependencies). In this paper, we propose a general model for the data-dependent loop scheduling problem on distributed as well as shared memory systems. In order to achieve load balancing and low runtime scheduling and communication overhead, our model is based on a loop task graph and the notion of critical path. In addition, we develop a heuristic algorithm based on our model and on genetic algorithms to test the reliability of the model. We test our approach on different scenarios and benchmarks. The results are very encouraging and suggest a future parallel compiler implementation based on our model.
机译：对于共享内存系统的并行循环调度问题，已经描述了许多方法，但是在与数据相关的循环调度问题（具有循环依赖项的嵌套循环）方面，所做的工作很少。在本文中，我们为分布式和共享存储系统上的数据相关循环调度问题提出了一个通用模型。为了实现负载平衡和较低的运行时调度和通信开销，我们的模型基于循环任务图和关键路径的概念。此外，我们基于模型和遗传算法开发了一种启发式算法，以测试模型的可靠性。我们在不同的场景和基准上测试我们的方法。结果非常令人鼓舞，并建议将来基于我们的模型的并行编译器实现。

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