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.

翻译：当前嵌入式系统专门设计用于运行多媒体应用。这类应用对系统性能与能耗均有显著影响。通过为目标应用集选择最优缓存配置，可对这两个指标进行优化。多目标优化有助于以独立方式最小化这两个相互冲突的指标。本文提出一种基于多目标进化算法的优化方法，能够针对给定应用集找到最佳缓存配置。为评估候选解的质量，优化算法的执行与静态分析方法相结合，使用多种成熟的仿真工具。结果表明，该优化框架能够为Mediabench应用获得优化后的缓存。与基准缓存相比，本设计方法在执行时间与能耗上分别实现了平均64.43%和91.69%的改进。