Exhaustive community enumeration on a cluster
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Description
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.
Keywords
Computer, programming, Computer, science, Cluster, of, workstations, clusters, Community, Finding, Load, imbalance, OpenMP, Parallelizations, Application, programming, interfaces, (API)