控制流图自动前瞻生成的性能分析:一些实验

Behrouz Zarei, Mike Pidd
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引用次数: 3

摘要

并行离散事件模型的性能高度依赖于前瞻性,特别是当采用保守算法时。不幸的是,已知前瞻是问题相关的,这限制了保守算法的实现。本文使用一个简单的排队网络来展示这种前瞻性如何影响性能,并讨论了使用控制流图(cfg)自动生成前瞻性的各种技术。在CRAY t3e1200e上对这些方法进行了排队网络仿真测试。结果表明,自动预查技术虽然需要一定的计算时间,但其性能与注入并行程序的最佳手动提取预查技术一样好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance analysis of automatic lookahead generation by control flow graph: some experiments

The performance of parallel discrete event models is highly dependent on lookahead, particularly when a conservative algorithm is employed. Unfortunately lookahead is known to be problem-dependent, which restricts the implementations of conservative algorithms. This paper uses a simple queuing network to show how this lookahead affects performance and discusses various techniques for automatic generation of lookahead using control flow graphs (CFGs). These methods are tested on the queuing network simulation running on a CRAY T3E 1200E. Results indicate that the automatic lookahead techniques, though requiring some time to compute, perform as well as the best manually extracted lookahead injected into the parallel program.

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