Exhaustive community enumeration on a cluster
Fecha
2018-01-01
Autores
Trefftz C.
McGuire H.
Kurmas Z.
Scripps J.
Pineda J.D.
Título de la revista
ISSN de la revista
Título del volumen
Editor
Institute of Electrical and Electronics Engineers Inc.
Resumen
A 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.