Domain Decomposition Based High Performance Parallel Computing

TL;DR

This paper explores the parallelization of finite element Navier-Stokes codes using domain decomposition and advanced sparse direct solvers to improve scalability and performance in high-performance computing environments.

Contribution

It introduces a domain decomposition approach combined with the PARDISO solver to enhance the parallel scalability of sparse direct solvers for fluid dynamics simulations.

Findings

Improved scalability of Navier-Stokes codes with domain decomposition

Effective use of PARDISO solver in parallel environments

Scalability tested for Newton and modified Newton algorithms

Abstract

The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers. Parallel sparse direct solvers are not found to exhibit good scalability. Hence, the parallelization of sparse direct solvers is done using domain decomposition techniques. A highly efficient sparse direct solver PARDISO is used in this study. The scalability of both Newton and modified Newton algorithms are tested.