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

arXiv: https://arxiv.org/abs/2302.11236 · HTML: https://mlsanity.com/paper/2302.11236/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 35 references that are in the map.
- First posted on arXiv 22 Feb 2023.

## Built on by (most cited first, 1 of 1)

- [Evolutionary Design of the Memory Subsystem](https://mlsanity.com/paper/2303.16074/) (2023)

## Abstract (arXiv)

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.