Guiding Hardware-Driven Turbo with Application Performance Awareness

D. Wilson, Asma H. Al-rawi, Lowren H. Lawson, Siddhartha Jana, Federico Ardanaz, J. Eastep, A. Coskun
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引用次数: 2

Abstract

Parallel programming across many CPU cores offers many challenges in software design, such as mitigating performance or efficiency loss in applications that reach synchronization points at varying times across the CPU cores. Existing solutions often aim to resolve this through clever optimizations in application design, or by reacting to the imbalance by throttling the CPU core frequency of the early-finishing cores at application run time. In this work, we propose a method to rebalance bulksynchronous MPI applications by selectively speeding up the latefinishing cores throughout application run time. This algorithm makes use of the new Intel® Speed Select Turbo Frequency feature that enables software to guide the hardware toward increasing the turbo frequency limits of some cores in exchange for decreased turbo frequency limits in other cores. We demonstrate up to 40% energy reduction and 17% execution time reduction in a highly-imbalanced, compute-bound benchmark application and up to 21% energy reduction with 5% execution time reduction in an imbalanced real-world application.
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引导硬件驱动Turbo与应用程序性能意识
跨多个CPU核心的并行编程为软件设计带来了许多挑战,例如,在跨CPU核心的不同时间到达同步点时,如何减轻应用程序的性能或效率损失。现有的解决方案通常旨在通过应用程序设计中的巧妙优化来解决这个问题,或者通过在应用程序运行时通过限制早期完成核心的CPU核心频率来对不平衡做出反应。在这项工作中,我们提出了一种方法,通过在整个应用程序运行时选择性地加速后期完成核心来重新平衡批量同步MPI应用程序。该算法利用新的英特尔®速度选择Turbo频率功能,使软件能够引导硬件增加某些核心的Turbo频率限制,以换取其他核心的Turbo频率限制降低。我们演示了在高度不平衡的计算约束基准应用程序中减少高达40%的能源和17%的执行时间,以及在不平衡的实际应用程序中减少高达21%的能源和5%的执行时间。
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