# Design and Analysis of a Task-based Parallelization over a Runtime System of an Explicit Finite-Volume CFD Code with Adaptive Time Stepping

## TL;DR

This paper presents a task-based parallelization approach for an explicit finite-volume CFD code with adaptive time stepping, aiming to reduce synchronization overhead and improve performance on large-scale simulations.

## Contribution

It introduces a novel task-based parallelization of FLUSEPA using StarPU, combining multiple levels of parallelism to enhance efficiency in aerodynamic simulations.

## Key findings

- Successful simulation of an 80-million-cell mesh for Ariane 5 blast wave
- Reduction in synchronization overhead compared to MPI/OpenMP implementation
- Demonstrated improved scalability and performance in large-scale CFD simulations

## Abstract

FLUSEPA (Registered trademark in France No. 134009261) is an advanced simulation tool which performs a large panel of aerodynamic studies. It is the unstructured finite-volume solver developed by Airbus Safran Launchers company to calculate compressible, multidimensional, unsteady, viscous and reactive flows around bodies in relative motion. The time integration in FLUSEPA is done using an explicit temporal adaptive method. The current production version of the code is based on MPI and OpenMP. This implementation leads to important synchronizations that must be reduced. To tackle this problem, we present the study of a task-based parallelization of the aerodynamic solver of FLUSEPA using the runtime system StarPU and combining up to three levels of parallelism. We validate our solution by the simulation (using a finite-volume mesh with 80 million cells) of a take-off blast wave propagation for Ariane 5 launcher.