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Speculative Parallelization Using Software Multi-threaded Transactions

机译:使用软件多线程事务进行投机并行化

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With the right techniques, multicore architectures may be able to continue the exponential performance trend that elevated the performance of applications of all types for decades. While many scientific programs can be parallelized without speculative techniques, speculative parallelism appears to be the key to continuing this trend for general-purpose applications. Recently-proposed code parallelization techniques, such as those by Bridges et al. and by Thies et al., demonstrate scalable performance on multiple cores by using speculation to divide code into atomic units (transactions) that span multiple threads in order to expose data parallelism. Unfortunately, most software and hardware Thread-Level Speculation (TLS) memory systems and transactional memories are not sufficient because they only support single-threaded atomic units. Multi-threaded Transactions (MTXs) address this problem, but they require expensive hardware support as currently proposed in the literature. This paper proposes a Software MTX (SMTX) system that captures the applicability and performance of hardware MTX, but on existing multicore machines. The SMTX system yields a harmonic mean speedup of 13.36x on native hardware with four 6-core processors (24 cores in total) running speculatively parallelized applications.
机译:使用正确的技术,多核体系结构可能能够延续数十年来提高所有类型应用程序性能的指数性能趋势。尽管许多科学程序无需推测性技术就可以并行化,但推测性并行性似乎是在通用应用程序中继续保持这一趋势的关键。最近提出的代码并行化技术,例如Br​​idges等人的技术。并且由Thies等人通过使用推测将代码划分为跨越多个线程的原子单元(事务)以展示数据并行性,展示了在多核上的可伸缩性能。不幸的是,大多数软件和硬件线程级推测(TLS)内存系统和事务性内存不足,因为它们仅支持单线程原子单元。多线程事务(MTX)解决了此问题,但是它们需要昂贵的硬件支持,如文献中当前提出的那样。本文提出了一个软件MTX(SMTX)系统,该系统可以捕获硬件MTX的适用性和性能,但是可以在现有的多核计算机上使用。 SMTX系统在运行推测性并行化应用程序的四个6核处理器(总共24个内核)的本地硬件上产生的谐波平均速度提高了13.36倍。

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