写后冻结:用LVars进行准确定性并行编程

L. Kuper, Aaron Turon, N. Krishnaswami, Ryan Newton
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引用次数: 54

摘要

按结构确定的并行编程模型提供了并行加速的优点,同时避免了困扰完全并发代码的不确定的、难以重现的bug。lvar提供了一种具有共享状态的按结构确定并行编程的原则方法:共享内存位置,其语义是根据特定于应用程序的晶格定义的。对LVar的写入取相对于晶格的旧值和新值的最小上界,而从LVar读取只能观察到其内容已超过晶格中的指定阈值。虽然它保证了决定论,但这个接口相当有限。我们以两种方式扩展lvar。首先,我们添加了“冻结”的功能,然后直接读取LVar的内容。其次,我们添加了将事件处理程序附加到LVar的功能,当LVar的值发生变化时触发回调。处理程序和冻结一起实现了一种富有表现力且有用的并行编程风格。我们证明,在通过这些扩展lvar进行通信的语言中,程序在最坏的情况下是准确定性的:每次运行时,它们要么产生相同的答案,要么引发错误。我们通过为Haskell实现一个支持各种基于lvar的数据结构的库,以及一个演示编程模型并产生有希望的并行加速的案例研究,来证明我们方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Freeze after writing: quasi-deterministic parallel programming with LVars
Deterministic-by-construction parallel programming models offer the advantages of parallel speedup while avoiding the nondeterministic, hard-to-reproduce bugs that plague fully concurrent code. A principled approach to deterministic-by-construction parallel programming with shared state is offered by LVars: shared memory locations whose semantics are defined in terms of an application-specific lattice. Writes to an LVar take the least upper bound of the old and new values with respect to the lattice, while reads from an LVar can observe only that its contents have crossed a specified threshold in the lattice. Although it guarantees determinism, this interface is quite limited. We extend LVars in two ways. First, we add the ability to "freeze" and then read the contents of an LVar directly. Second, we add the ability to attach event handlers to an LVar, triggering a callback when the LVar's value changes. Together, handlers and freezing enable an expressive and useful style of parallel programming. We prove that in a language where communication takes place through these extended LVars, programs are at worst quasi-deterministic: on every run, they either produce the same answer or raise an error. We demonstrate the viability of our approach by implementing a library for Haskell supporting a variety of LVar-based data structures, together with a case study that illustrates the programming model and yields promising parallel speedup.
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