Analysis of the Performance of Genetic Algorithm Parallelized with OpenMP Through Execution Traces

Gabriella Lopes Andrade, Marcia Cristina Cera


Run tracing allows you to identify issues affecting the performance of parallel applications. This work consists in evaluating the parallelization of a Genetic Algorithm applied to the Vehicle Routing Problem with OpenMP, where the performance obtained was not ideally expected. Being that it was possible to obtain a performance increase of 1.4 times in the architecture used, however, but still below ideal. Therefore, the general objective of this work is to investigate the causes of the low performance obtained by the Genetic Algorithm, performing an analysis from the execution traces. Our results showed that the parallelization of the Genetic Algorithm is according to the model in which it was implemented and to the set of instances of the target Vehicle Routing Problem used.


Genetic Algorithms; OpenMP; Paralelization; Performance; Score-P; Tracking; Vampir; Vehicle Routing Problem

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