Thread Affinity in Software Transactional Memory

Douglas Pereira Pasqualin, M. Diener, A. R. D. Bois, M. Pilla
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引用次数: 4

Abstract

Software Transactional Memory (STM) is an abstraction to synchronize accesses to shared resources. It simplifies parallel programming by replacing the use of explicit locks and synchronization mechanisms with atomic blocks. A wellknown approach to improve performance of STM applications is to serialize transactions to avoid conflicts using schedulers and mapping algorithms. However, in current architectures with complex memory hierarchies it is also important to consider where the memory of the program is allocated and how it is accessed. An important technique for improving memory locality is to map threads and data of an application based on their memory access behavior. This technique is called sharing-aware mapping. In this paper, we introduce a method to detect sharing behavior directly inside the STM library by tracking and analyzing how threads perform STM operations. This information is then used to perform an optimized mapping of the application's threads to cores in order to improve the efficiency of STM operations. Experimental results with the STAMP benchmarks show performance gains of up to 9.7x (1.4x on average), and a reduction of the number of aborts of up to 8.5x, compared to the Linux scheduler.
软件事务性内存中的线程关联
软件事务性内存(STM)是一种用于同步访问共享资源的抽象。它通过用原子块取代显式锁和同步机制来简化并行编程。提高STM应用程序性能的一种众所周知的方法是使用调度器和映射算法序列化事务以避免冲突。然而,在当前具有复杂内存层次结构的体系结构中,考虑程序的内存分配位置和访问方式也很重要。改善内存局部性的一项重要技术是根据应用程序的内存访问行为映射线程和数据。这种技术称为共享感知映射。在本文中,我们介绍了一种通过跟踪和分析线程如何执行STM操作来直接检测STM库中的共享行为的方法。然后使用此信息执行应用程序线程到内核的优化映射,以提高STM操作的效率。使用STAMP基准测试的实验结果显示,与Linux调度器相比,性能提高了9.7倍(平均1.4倍),中止次数减少了8.5倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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