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Estimating the Worst-Case Energy Consumption of Embedded Software

机译:估算嵌入式软件的最坏情况能耗

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The evolution of battery technology is not being able to keep up with the increasing performance demand of mobile embedded systems. Therefore, battery life has become an important design constraint. As battery-operated embedded devices are deployed in mission critical systems, designers should ensure that the energy constraints are satisfied in addition to the timing constraints — the battery should not drain out before a critical task completes execution. Giving these guarantees requires the knowledge of the worst-case execution time and energy of a task. Significant progress has been made in estimating the worst-case execution time through static analysis. In contrast, existing energy estimation techniques use average-case execution profile of a program and as such cannot guarantee the satisfiability of energy constraints. In this paper, we present a static analysis technique to estimate the worst-case energy consumption of a task on complex micro-architectures. Estimating a bound on energy is non-trivial as it is unsafe to assume any direct correlation with the bound on execution time. Experimental evaluation with a number of benchmark programs indicates the accuracy of our worst-case energy consumption estimates.
机译:电池技术的发展无法跟上移动嵌入式系统不断增长的性能需求。因此,电池寿命已成为重要的设计约束。当将电池供电的嵌入式设备部署在关键任务系统中时,设计人员应确保除了时序约束之外还满足能量约束-关键任务完成执行之前,电池不应耗尽。提供这些保证要求了解最坏情况下的执行时间和任务的能量。通过静态分析估计最坏情况下的执行时间已经取得了重大进展。相反,现有的能量估计技术使用程序的平均情况执行配置文件,因此不能保证能量约束的可满足性。在本文中,我们提出了一种静态分析技术来估算复杂微体系结构上的任务的最坏情况能耗。估计能量的界限并非易事,因为假定与执行时间的界限直接相关是不安全的。通过一些基准程序进行的实验评估表明,我们最坏情况下的能耗估算值是准确的。

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