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Characterizing Fine-Grain Parallelism on Modern Multicore Platform

机译:在现代多核平台上表征细粒度并行

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Since chip multiprocessors have dominated the processor market, developing a parallel programming model with proper trade-off between productivity and efficiency become increasingly important. As a typical fine-grain parallelism model, Intel Threading Building Blocks (TBB) simplifies parallel programming by runtime schedule. Despite its simplicity, it costs non-trivial runtime overhead which may increase as the thread counts increase. In this work, we conduct an experiment on real commodity hardware to evaluate performance scalability of TBB using PARSEC benchmark suite. We first compare TBB with Pthreads to show that TBB applications can achieve comparable performance as Pthreads applications. To find the performance bottleneck of TBB applications, we measure the runtime overhead of TBB focused on 3 basic TBB runtime activities. The result provides valuable implications which can be used to develop scalable runtime libraries and architectural support for alleviating performance bottlenecks.
机译:由于芯片多处理器已经在处理器市场上占据了主导地位,因此开发一种并行编程模型并在生产率和效率之间进行适当的权衡变得越来越重要。作为典型的细粒度并行模型,英特尔线程构建模块(TBB)可以根据运行时计划简化并行编程。尽管它很简单,但是它花费了不小的运行时间开销,随着线程数的增加,它可能会增加。在这项工作中,我们对真实的商品硬件进行了实验,以使用PARSEC基准套件评估TBB的性能可扩展性。我们首先将TBB与Pthreads进行比较,以证明TBB应用程序可以实现与Pthreads应用程序相当的性能。为了找到TBB应用程序的性能瓶颈,我们以3个基本的TBB运行时活动为重点来衡量TBB的运行时开销。结果提供了宝贵的启示,可用于开发可扩展的运行时库和体系结构支持以减轻性能瓶颈。

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