MVAPICH2 vs. OpenMPI for a Clustering Algorithm

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Affinity propagation is a clustering algorithm that functions by identifying similar data points in an iterative process. Its structure allows for taking full advantage of parallel computing to enable the solution of larger problems and to solve them faster than possible in serial. We present a memory-optimal implementation with minimal number of communication commands and demonstrate its excellent scalability. Additionally, we present a comparison of two implementations of MPI that demonstrate that MVAPICH2 exhibits better scalability up to larger numbers of parallel processes than OpenMPI for this code.