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Distributed Models of Thread-Level Speculation

机译:线程级推测的分布式模型

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摘要

Thread-level speculation is an aggressive par-allelization technique that can extract parallelism from code which is not provably free of data dependencies. This paper introduces a novel application of thread-level speculation to a distributed heterogeneous environment We propose and evaluate two speculative models which attempt to reduce some of the remote method invocation overhead associated with distributed objects. Our evaluation of the application of thread-level speculation to client-server applications resulted in substantial performance increases, on the order of 3 times for our initial model, and 21 times for the second.
机译:线程级推测是一种积极的par-alleization技术,可以从代码中提取并行性,而这种并行性并不能证明没有数据依赖性。本文介绍了线程级推测在分布式异构环境中的新应用。我们提出并评估了两个推测模型,这些模型试图减少与分布式对象相关的某些远程方法调用开销。我们对线程级推测对客户端-服务器应用程序的应用程序的评估导致性能显着提高,初始模型的性能提高了大约3倍,第二次提高了21倍。

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