On the infeasibility of analysing worst-case dynamic energy
On the infeasibility of analysing worst-case dynamic energy
复制标题
论分析最坏情况动态能量的不可行性
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
K. Eder
中科院分区：
文献类型：
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作者：
J. Morse;Steve Kerrison;K. Eder
在本文中，我们研究了适合物联网（IoT）域的微处理器执行软件的动态能量来源。通过执行软件估算所消耗的能量通常是通过根据处理器的某些能量模型来确定程序中最昂贵的路径来实现的。但是，很少有模型能够充分解决操作数数据引起的动态能量问题。我们发现，操作数数据对总体能量的贡献可能很重要，证明发现最差的输入数据是NP-HARD，并且进一步无法估计任何有用的因素。我们的工作表明，准确的数据依赖能量分析是不可行的，应考虑其他能量估计的技术。
In this paper we study the sources of dynamic energy during the execution of software on microprocessors suited for the Internet of Things (IoT) domain. Estimating the energy consumed by executing software is typically achieved by determining the most costly path through the program according to some energy model of the processor. Few models, however, adequately tackle the matter of dynamic energy caused by operand data. We find that the contribution of operand data to overall energy can be significant, prove that finding the worst-case input data is NP-hard, and further, that it cannot be estimated to any useful factor. Our work shows that accurate worst-case analysis of data dependent energy is infeasible, and that other techniques for energy estimation should be considered.