异构多核心系统的加速和功率缩放模型

Ashur Rafiev;Mohammed A. N. Al-Hayanni;Fei Xia;Rishad Shafik;Alexander Romanovsky;Alex Yakovlev
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引用次数: 13

摘要

传统的加速模型,如Amdahl定律、Gustafson定律以及Sun和Ni定律,有助于研究界和行业更好地理解系统性能和应用程序并行性。由于它们主要针对同质硬件平台或有限形式的处理器异构性,因此这些模型不涵盖新出现的多核异构架构。本文报告了基于更通用的异构表示(称为范式异构)的新型加速和能耗模型,该模型支持广泛的异构多核心架构。该建模方法旨在预测系统功率效率和性能范围,并促进硬件和系统软件层面的研究和开发。这些模型是通过在现成的大屏幕上进行大量实验来验证的。小型异构平台和双GPU笔记本电脑,加速平均误差为1%,功耗平均误差小于6.5%。针对Odroid XU3平台上的系统负载均衡器进行了定量效率分析,以证明该方法的实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speedup and Power Scaling Models for Heterogeneous Many-Core Systems
Traditional speedup models, such as Amdahl's law, Gustafson's, and Sun and Ni's, have helped the research community and industry better understand system performance capabilities and application parallelizability. As they mostly target homogeneous hardware platforms or limited forms of processor heterogeneity, these models do not cover newly emerging multi-core heterogeneous architectures. This paper reports on novel speedup and energy consumption models based on a more general representation of heterogeneity, referred to as the normal form heterogeneity, that supports a wide range of heterogeneous many-core architectures. The modelling method aims to predict system power efficiency and performance ranges, and facilitates research and development at the hardware and system software levels. The models were validated through extensive experimentation on the off-the-shelf big. LITTLE heterogeneous platform and a dual-GPU laptop, with an average error of 1 percent for speedup and of less than 6.5 percent for power dissipation. A quantitative efficiency analysis targeting the system load balancer on the Odroid XU3 platform was used to demonstrate the practical use of the method.
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