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Detecting, Exposing, and Classifying Sequential Consistency Violations

机译:检测,暴露和分类顺序一致性违规

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Sequential Consistency (SC) is the most intuitive memory model for parallel programs. However, modern architectures aggressively reorder and overlap memory accesses, causing SC violations. An SC violation is virtually always a bug. Most prior schemes either search the entire state space of a program, or use a constraint solver to find SC violations. A promising recent scheme uses active testing technique but fails to be effective for SC violations involving larger number of threads and variables, and larger codebases. We propose Orion, the first active testing technique that can detect, expose, and classify any arbitrary SC violations in any program. Orion works in two phases. In the first phase, it finds potential SC violation cycles by focusing on racing accesses. In the second phase, it exposes each SC violation cycle by enforcing the exact scheduling order. We present a detailed design of Orion in the paper. We tested different concurrent algorithms, bug kernels, SPLASH2, PARSEC applications, and an open source program, Apache. We experimented with TSO and PSO memory models. We detected and exposed 60 SC violations of which 15 violations involve more than two processors and variables. Orion exposes SC violations quickly and with high probability. Compared to a state-of-the-art active testing technique, it has a much better SC violation detection ability.
机译:顺序一致性(SC)是并行程序最直观的内存模型。但是,现代体系结构主动地对内存访问进行重新排序并使其重叠,从而导致SC冲突。违反SC几乎总是一个错误。大多数现有方案要么搜索程序的整个状态空间,要么使用约束求解器查找SC违规。最近有希望的方案使用主动测试技术,但对于涉及大量线程和变量以及较大代码库的SC违规无效。我们提出了Orion,这是第一种主动检测技术,可以检测,暴露和分类任何程序中的任意SC违规。 Orion分两个阶段工作。在第一阶段,它通过关注赛车通道来发现潜在的SC违规周期。在第二阶段,它通过执行确切的调度顺序来公开每个SC违规周期。我们在本文中介绍了Orion的详细设计。我们测试了不同的并发算法,错误内核,SPLASH2,PARSEC应用程序和开源程序Apache。我们尝试了TSO和PSO内存模型。我们检测到并暴露了60个SC违规,其中15个违规涉及两个以上的处理器和变量。 Orion极有可能迅速揭露违反SC的行为。与最新的主动测试技术相比,它具有更好的SC违规检测能力。

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