Memory Consistency and Program Transformations

Akshay GopalakrishnanMcGill University, Clark VerbruggeMcGill University, Mark BattyUniversity of Kent
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Abstract

A memory consistency model specifies the allowed behaviors of shared memory concurrent programs. At the language level, these models are known to have a non-trivial impact on the safety of program optimizations, limiting the ability to rearrange/refactor code without introducing new behaviors. Existing programming language memory models try to address this by permitting more (relaxed/weak) concurrent behaviors but are still unable to allow all the desired optimizations. A core problem is that weaker consistency models may also render optimizations unsafe, a conclusion that goes against the intuition of them allowing more behaviors. This exposes an open problem of the compositional interaction between memory consistency semantics and optimizations: which parts of the semantics correspond to allowing/disallowing which set of optimizations is unclear. In this work, we establish a formal foundation suitable enough to understand this compositional nature, decomposing optimizations into a finite set of elementary effects on program execution traces, over which aspects of safety can be assessed. We use this decomposition to identify a desirable compositional property (complete) that would guarantee the safety of optimizations from one memory model to another. We showcase its practicality by proving such a property between Sequential Consistency (SC) and $SC_{RR}$, the latter allowing independent read-read reordering over $SC$. Our work potentially paves way to a new design methodology of programming-language memory models, one that places emphasis on the optimizations desired to be performed.
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内存一致性和程序转换
内存一致性模型规定了共享内存并发程序允许的行为。众所周知,在语言层面,这些模型会对程序优化的安全性产生非同小可的影响,从而限制了在不引入新行为的情况下重新排列/重构代码的能力。现有的编程语言内存模型试图通过允许更多并发行为(宽松/弱化)来解决这个问题,但仍然无法实现所有期望的优化。一个核心问题是,较弱的一致性模型也可能使优化变得不安全,而这一结论与允许更多行为的直觉相悖。这就暴露了内存一致性语义和优化之间的组合交互这一未决问题:语义的哪些部分对应于允许/不允许哪一组优化,这一点并不清楚。在这项工作中,我们建立了一个足以理解这种组合性质的形式基础,将优化分解为对程序执行轨迹的一系列有限的基本影响,通过这些影响可以评估安全性的各个方面。我们利用这种分解来确定一种理想的组合特性(完全性),它可以保证从一种内存模型到另一种内存模型的优化的安全性。我们通过证明连续一致性(SC)和$SC_{RR}$之间的这种属性来展示它的实用性,后者允许在$SC$上进行独立的读取重排序。我们的工作有可能为编程语言内存模型的新设计方法铺平道路,这种方法的重点是希望实现的优化。
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