Current embedded systems are specifically designed to run multimedia applications. These applications have a big impact on both performance and energy consumption. Both metrics can be optimized selecting the best cache configuration for a target set of applications. Multi-objective optimization may help to minimize both conflicting metrics in an independent manner. In this work, we propose an optimization method that based on Multi-Objective Evolutionary Algorithms, is able to find the best cache configuration for a given set of applications. To evaluate the goodness of candidate solutions, the execution of the optimization algorithm is combined with a static profiling methodology using several well-known simulation tools. Results show that our optimization framework is able to obtain an optimized cache for Mediabench applications. Compared to a baseline cache memory, our design method reaches an average improvement of 64.43\% and 91.69\% in execution time and energy consumption, respectively.

本文提出一种基于多目标进化算法的优化方法，以在给定一组应用程序的情况下寻找最佳缓存配置，结果显示我们的优化框架能够获得针对 Mediabench 应用程序的优化缓存，与基线缓存相比，我们的设计方法在执行时间和能耗上平均分别提高了64.43％和91.69％。

嵌入式系统单层缓存存储器能量消耗和执行时间的多目标优化