在软件事务性内存系统中编译器的帮助下处理冲突

Sandya Mannarswamy, R. Govindarajan
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引用次数: 3

摘要

软件通过使用软件事务性内存(software Transactional Memory, STM)来实现乐观并发,从而支持原子段。然而,STM实现带来了很高的开销,这减少了程序员对这种方法的广泛使用。冲突是stm开销的主要来源。事务性内存系统的基本性能前提是乐观并发原则,其中事务执行的数据更新是针对不相交的对象/内存位置,称为不相交访问并行(DAP)。否则,更新将发生冲突,并且除一个事务外的所有事务都将终止。这样的中止会导致工作浪费和性能下降。虽然STM实现中的争用管理系统试图通过各种运行时反馈控制机制来减少冲突,但它们并不知道应用程序的结构和数据访问模式,因此通常在冲突发生后才采取行动。本文提出了一种基于编译器分析的静态原子段识别方案,该方案可以识别出在多个线程并发执行时实例总是冲突的静态原子段。这样的原子段称为总是冲突原子段(ACAS)。我们提出并评估了选择性悲观并发控制(SPCC)和编译器插入的早期冲突检查(ECC)两种技术,这两种技术可以帮助减少ACAS引起的STM开销。我们表明,这些技术有助于将STAMP基准测试中的4个中断减少27.52%,同时将性能提高1.24%至19.31%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Handling Conflicts with Compiler's Help in Software Transactional Memory Systems
Atomic sections are supported in software through the use of optimistic concurrency by using Software Transactional Memory (STM). However STM implementations incur high overheads which reduce the wide-spread use of this approach by programmers. Conflicts are a major source of overheads in STMs. The basic performance premise of a transactional memory system is the optimistic concurrency principle wherein data updates executed by the transactions are to disjoint objects/memory locations, referred to as Disjoint Access Parallel (DAP). Otherwise, the updates conflict, and all but one of the transactions are aborted. Such aborts result in wasted work and performance degradation. While contention management systems in STM implementations try to reduce conflicts by various runtime feedback control mechanisms, they are not aware of the application’s structure and data access patterns and hence typically act after the conflicts have occurred. In this paper we propose a scheme based on compiler analysis, which can identify static atomic sections whose instances, when executed concurrently by more than one thread always conflict. Such an atomic section is referred to as Always Conflicting Atomic Section (ACAS). We propose and evaluate two techniques Selective Pessimistic Concurrency Control (SPCC) and compiler inserted Early Conflict Checks (ECC) which can help reduce the STM overheads caused by ACAS. We show that these techniques help reduce the aborts in 4 of the STAMP benchmarks by up to 27.52% while improving performance by 1.24% to 19.31%.
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