论最坏情况加工动态能量分析的局限性
On the limitations of analysing worst-case dynamic energy of processing
摘要：
本文研究了在深度嵌入式微处理器上软件执行期间由数据引起的动态能耗，这在某些设备上可能很重要。在最坏情况下的能量消耗分析中，能量模型被用来找到最昂贵的执行路径。采用每条指令的最坏情况能量产生一个安全但过于悲观的上限。安全和严格边界的算法将是可取的。我们发现，找到确切的最坏情况下的能量是NP-困难的，紧界不能近似保证安全。我们的结论是，任何能源模型的目标紧密性必须要么牺牲安全性或接受过度近似成比例的数据依赖的能源。
英文摘要：
This paper examines dynamic energy consumption caused by data during software execution on deeply embedded microprocessors, which can be significant on some devices. In worst-case energy consumption analysis, energy models are used to find the most costly execution path. Taking each instruction's worst case energy produces a safe but overly pessimistic upper bound. Algorithms for safe and tight bounds would be desirable. We show that finding exact worst-case energy is NP-hard, and that tight bounds cannot be approximated with guaranteed safety. We conclude that any energy model targeting tightness must either sacrifice safety or accept overapproximation proportional to data-dependent energy.
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