Improving Performance on Atmospheric Models through a Hybrid OpenMP/MPI Implementation

Abstract

This work shows how a Hybrid MPI/OpenMP implementation can improve the performance of the Ocean-Land-Atmosphere Model (OLAM) on a multi-core cluster environment, which is a typical HPC many small files workload application. Previous experiments have shown that the scalability of this application on clusters is limited by the performance of the output operations. We show that the Hybrid MPI/OpenMP version of OLAM decreases the number of output files, resulting in better performance for I/O operations. We also observe that the MPI version of OLAM performs better for unbalanced workloads and that further parallel optimizations should be included on the hybrid version in order to improve the parallel execution time of OLAM.