A PETSc parallel-in-time solver based on MGRIT algorithm

We address the development of a modular implementation of the MGRIT (MultiGrid-In-Time) algorithm to solve linear and nonlinear systems that arise from the discretization of evolutionary models with a parallel-in-time approach in the context of the PETSc (the Portable, Extensible Toolkit for Scientific computing) library. Our aim is to give the opportunity of predicting the performance gain achievable when using the MGRIT approach instead of the Time Stepping integrator (TS). To this end, we analyze the performance parameters of the algorithm that provide a-priori the best number of processing elements and grid levels to use to address the scaling of MGRIT, regarded as a parallel iterative algorithm proceeding along the time dimensio

Insertion of PETSc in the NEMO stack software. Driving NEMO towards Exascale Computing

This paper addresses the scientific challenges related to high level implementation strategies which steer the NEMO (Nucleus for European Modelling of the Ocean) code toward the effective exploitation of the opportunities offered by exascale systems. We consider, as case studies, two components of the NEMO ocean model (OPA-Ocean PArallelization): the Sea Surface Height equation solver and the Variational Data Assimilation module. The advantages rising from the insertion of consolidated scientific libraries in the NEMO code are highlighted: such advantages concern both the “software quality” improvement (see the software quality parameters like robustness, portability, resilience, etc.) and the reduction of time spent for software development and maintenance. Finally, we consider the Shallow Water equations as a toy model for NEMO ocean model to show how the use of PETSc objects predisposes the application to gain a good level of scalability and efficiency when the most suitable level of abstraction is used