English

Multi-objective optimization of energy consumption and execution time in a single level cache memory for embedded systems

Neural and Evolutionary Computing 2023-02-23 v1 Artificial Intelligence

Abstract

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.

Keywords

Cite

@article{arxiv.2302.11236,
  title  = {Multi-objective optimization of energy consumption and execution time in a single level cache memory for embedded systems},
  author = {Josefa Díaz Álvarez and José L. Risco-Martín and J. Manuel Colmenar},
  journal= {arXiv preprint arXiv:2302.11236},
  year   = {2023}
}
R2 v1 2026-06-28T08:46:35.548Z