2021-04-122018-01-019781538646496WOS;000451221100037SCOPUS;2-s2.0-85047324366http://hdl.handle.net/10784/28770A 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.engInstitute of Electrical and Electronics Engineers Inc.info:eu-repo/semantics/conferencePaperComputerprogrammingComputerscienceClusterofworkstationsclustersCommunityFindingLoadimbalanceOpenMPParallelizationsApplicationprogramminginterfaces(API)2021-04-12Trefftz C.McGuire H.Kurmas Z.Scripps J.Pineda J.D.10.1109/CCWC.2018.8301644