A Study on the Influence of Software and Hardware Features on Program Energy

A. Rajan, Adel Noureddine, Panagiotis Stratis
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引用次数: 2

Abstract

Software energy consumption has emerged as a growing concern in recent years. Managing the energy consumed by a software is, however, a difficult challenge due to the large number of factors affecting it -- namely, features of the processor, memory, cache, and other hardware components, characteristics of the program and the workload running, OS routines, compiler optimisations, among others. In this paper we study the relevance of numerous architectural and program features (static and dynamic) to the energy consumed by software. The motivation behind the study is to gain an understanding of the features affecting software energy and to provide recommendations on features to optimise for energy efficiency. In our study we used 58 subject desktop programs, each with their own workload, and from different application domains. We collected over 100 hardware and software metrics, statically and dynamically, using existing tools for program analysis, instrumentation and run time monitoring. We then performed statistical feature selection to extract the features relevant to energy consumption. We discuss potential optimisations for the selected features. We also examine whether the energy-relevant features are different from those known to affect software performance. The features commonly selected in our experiments were execution time, cache accesses, memory instructions, context switches, CPU migrations, and program length (Halstead metric). All of these features are known to affect software performance, in terms of running time, power consumed and latency.
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软件和硬件特性对程序能量影响的研究
近年来,软件能耗问题日益受到关注。然而,管理软件消耗的能量是一项艰巨的挑战,因为影响它的因素很多——即处理器、内存、缓存和其他硬件组件的特性、程序和工作负载运行的特性、操作系统例程、编译器优化等等。在本文中,我们研究了许多架构和程序特性(静态和动态)与软件能耗的相关性。这项研究背后的动机是了解影响软件能量的特性,并提供关于优化能源效率的特性的建议。在我们的研究中,我们使用了58个主题桌面程序,每个程序都有自己的工作负载,并且来自不同的应用领域。我们收集了超过100个硬件和软件指标,静态和动态的,使用现有的工具进行程序分析,仪器和运行时监控。然后进行统计特征选择,提取与能耗相关的特征。我们讨论了所选特性的潜在优化。我们还研究了与能源相关的特性是否与那些已知的影响软件性能的特性不同。在我们的实验中,通常选择的特征是执行时间、缓存访问、内存指令、上下文切换、CPU迁移和程序长度(Halstead度量)。众所周知,所有这些特性都会影响软件性能,包括运行时间、功耗和延迟。
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