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Online Sharing-Aware Thread Mapping in Software Transactional Memory

机译:软件事务内存中的在线共享感知线程映射

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Software Transactional Memory (STM) is an alternative abstraction to synchronize processes in parallel programming. One advantage is simplicity since it is possible to replace the use of explicit locks with atomic blocks. Regarding STM performance, many studies already have been made focusing on reducing the number of aborts. However, in current multicore architectures with complex memory hierarchies, it is also important to consider where the memory of a program is allocated and how it is accessed. This paper proposes the use of a technique called sharing-aware mapping, which maps threads to cores of an application based on their memory access behavior, to achieve better performance in STM systems. We introduce STMap, an online, low overhead mechanism to detect the sharing behavior and perform the mapping directly inside the STM library, by tracking and analyzing how threads perform STM operations. In experiments with the STAMP benchmark suite and synthetic benchmarks, STMap shows performance gains of up to 77% on a Xeon system (17.5% on average) and 85% on an Opteron system (9.1% on average), compared to the Linux scheduler.
机译:软件事务性内存(STM)是在并行编程中同步进程的替代抽象。一个优点是简单,因为可以用原子块代替显式锁。关于STM性能,已经进行了许多研究,着重于减少中止次数。但是,在当前具有复杂内存层次结构的多核体系结构中,考虑程序的内存分配位置和访问方式也很重要。本文提出使用一种称为共享感知映射的技术,该技术根据线程的内存访问行为将线程映射到应用程序的核心,以在STM系统中实现更好的性能。我们引入STMap,这是一种在线,低开销的机制,可通过跟踪和分析线程如何执行STM操作来检测共享行为并直接在STM库内部执行映射。与Linux调度程序相比,在使用STAMP基准套件和综合基准进行的实验中,STMap显示在Xeon系统上的性能提升高达77%(平均17.5%),在Opteron系统上的性能提升高达85%(平均9.1%)。

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