Performance and results of the high-resolution biogeochemical model PELAGOS025 v1.0 within NEMO v3.4

The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the Nucleus for the European Modelling of the Ocean (NEMO) physical ocean model and the Biogeochemical Flux Model (BFM) biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at the CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach.

Performance and results of the high-resolution biogeochemical model PELAGOS025 within NEMO

The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the physical ocean model NEMO and the BFM biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach.