Hybrid parallelization may be the only path for most codes to use HPC systems on a very large scale. Even within a small scale, with an increasing number of cores per node, combining MPI with some shared memory thread-based library allows to reduce the application network requirements. Despite the benefits of a hybrid approach, it is not easy to achieve an efficient hybrid execution. This is not only because of the added complexity of combining two different programming models, but also because in many cases the code was initially designed with just one level of parallelization and later extended to a hybrid mode. This paper presents our model to diagnose the efficiency of hybrid applications, distinguishing the contribution of each parallel programming paradigm. The flexibility of the proposed methodology allows us to use it for different paradigms and scenarios, like comparing the MPI+OpenMP and MPI+CUDA versions of the same code.

This work has been partially developed under the scope of POP CoE which has received funding from the European Union´s Horizon 2020 research and innovation programme (under grant agreements No. 676553 and 824080), and with the support of the Comision Interministerial de Ciencia y Tecnología (CICYT) under contract No. PID2019- 107255GB-C22. We also want to acknowledge the ChEESE CoE and the EDANYA group from Universidad de Málaga (www.uma.es/edanya) that granted us permission to report on the Tsunami-HySEA analysis.

Peer Reviewed