Universidad EAFIT. Departamento de Ingeniería de SistemasI+D+I en Tecnologías de la Información y las Comunicaciones2023-11-212023-11-21http://repository-salesiana.heoq.net/handle/123456789/309783A parallelization based on MPI and OpenMP of an algorithm that evaluates and counts all the possible communities of a graph is presented. Performance results of the parallelization of the algorithm obtained on a cluster of workstations are reported. Load balancing was used to improve the speedups obtained on the cluster. Two different kinds of load balancing approaches were used: One that involved only MPI and a second one in which MPI and OpenMP were combined. The reason for the load imbalance is described. © 2018 IEEE.Institute of Electrical and Electronics Engineers Inc.ComputerprogrammingComputerscienceClusterofworkstationsclustersCommunityFindingLoadimbalanceOpenMPParallelizationsApplicationprogramminginterfaces(API)info:eu-repo/semantics/conferencePaper