@misc{10481/91923,
year = {2024},
month = {5},
url = {https://hdl.handle.net/10481/91923},
abstract = {Managing energy resources in scientific computing implies awareness of a wide range of software engineering techniques that, when applied, can minimize the energy footprint of experiments. In the case of evolutionary computation, we are talking about a specific workload that includes the generation of chromosomes and operations that change parts of them or access and operate on them to obtain a fitness value. In a low-level language such as Zig, we will show how different choices will affect the energy consumption of an experiment.},
organization = {PID2020-115570GB-C22 (DemocratAI::UGR)},
keywords = {Green computing},
keywords = {Metaheuristic},
keywords = {Energy-aware computing},
keywords = {Evolutionary algorithms},
keywords = {Zig},
title = {Minimizing evolutionary algorithms energy consumption in the low-level language Zig},
author = {Merelo Guervós, Juan Julián},
}