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.
['Carla Osthoff', 'Pablo Javier Grunmann', 'Francieli Zanon Boito', 'Rodrigo Virote Kassick', 'Laércio Lima Pilla', 'Philippe Olivier Alexandre Navaux', 'Claudio Schepke', 'Jairo Panetta', 'Nicolas Maillard', 'Pedro Leite da Silva Dias', 'Robert L. Walko']
Improving Performance on Atmospheric Models through a Hybrid OpenMP/MPI Implementation