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Squashing Alternatives for Software-Based Speculative Parallelization

机译:基于软件的推测并行化的压制替代方案

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Speculative parallelization is a runtime technique that optimistically executes sequential code in parallel, checking that no dependence violations arise. In the case of a dependence violation, all mechanisms proposed so far either switch to sequential execution, or conservatively stop and restart the offending thread and all its successors, potentially discarding work that does not depend on this particular violation. In this work we systematically explore the design space of solutions for this problem, proposing a new mechanism that reduces the number of threads that should be restarted when a data dependence violation is found. Our new solution, called exclusive squashing, keeps track of inter-thread dependencies at runtime, selectively stopping and restarting offending threads, together with all threads that have consumed data from them. We have compared this new approach with existent solutions on a real system, executing different applications with loops that are not analyzable at compile time and present as much as 10% of inter-thread dependence violations at runtime. Our experimental results show a relative performance improvement of up to 14%, together with a reduction of one-third of the numbers of squashed threads. The speculative parallelization scheme and benchmarks described in this paper are available under request.
机译:推测并行化是一种运行时技术,它可以并行地乐观地执行顺序代码,并检查没有发生依赖冲突。在依赖冲突的情况下,到目前为止提出的所有机制要么切换到顺序执行,要么保守地停止并重新启动有问题的线程及其所有后继者,从而有可能丢弃不依赖于此特定冲突的工作。在这项工作中,我们系统地探索了此问题的解决方案的设计空间,提出了一种新的机制,该机制减少了发现数据依赖冲突时应重新启动的线程数。我们的新解决方案称为“排他性挤压”,它在运行时跟踪线程间的依存关系,有选择地停止和重新启动有问题的线程,以及从中消耗数据的所有线程。我们已经将该新方法与实际系统上的现有解决方案进行了比较,它们使用在编译时无法分析的循环执行不同的应用程序,并且在运行时出现多达10%的线程间相关性违规。我们的实验结果表明,相对性能提高了14%,同时压扁的螺纹数量减少了三分之一。可根据要求提供本文所述的推测性并行化方案和基准。

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