Helping Developers Write Energy Efficient Haskell through a Data-Structure Evaluation

Gilberto Melfe, Alcides Fonseca, J. Fernandes
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引用次数: 11

Abstract

How a program is written has implications in the energy consumption of the running system, with economical and environmental consequences. In this context, understanding the energy consumption of operations on data-structures is crucial when optimizing software to execute under power constricted environments. Existing studies have not focused on the different components of energy consumption that processors expose, rather considering the global consumption. To understand the relationship between CPU and memory energy consumptions with execution time, we instrument a microbenchmark suite to collect such values, and we analyze the results. Our benchmark suite is comprised of 16 implementations of functional sequences, collections and associative collections while measuring detailed energy and time metrics. We further investigate the energy consumption impact of using different compilation optimizations. We have concluded that energy consumption is directly proportional to execution time. Additionally, DRAM and Package energy consumptions are directly proportional, with the DRAM representing between 15 and 31% of the total energy consumption. Finally, we also conclude that optimizations can have both a positive or a negative impact on energy consumption.
通过数据结构评估帮助开发人员编写节能的Haskell
程序的编写方式会影响运行系统的能源消耗,从而对经济和环境产生影响。在这种情况下,在优化软件以使其在功率受限的环境下执行时,了解数据结构操作的能耗是至关重要的。现有的研究并没有关注加工者所暴露的能源消耗的不同组成部分,而是考虑到全球的消耗。为了理解CPU和内存能耗与执行时间之间的关系,我们使用了一个微基准套件来收集这些值,并对结果进行分析。我们的基准测试套件由16个功能序列、集合和关联集合的实现组成,同时测量详细的能量和时间指标。我们进一步研究了使用不同的编译优化对能耗的影响。我们得出的结论是,能量消耗与执行时间成正比。此外,DRAM和封装能耗成正比,其中DRAM占总能耗的15%至31%。最后,我们还得出结论,优化可以对能源消耗产生积极或消极的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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