nSharma: Numerical Simulation Heterogeneity Aware Runtime Manager for OpenFOAM

Abstract

CFD simulations are a fundamental engineering application, implying huge workloads, often with dynamic behaviour due to runtime mesh refinement. Parallel processing over heterogeneous distributed memory clusters is often used to process such workloads. The execution of dynamic workloads over a set of heterogeneous resources leads to load imbalances that severely impacts execution time, when static uniform load distribution is used. This paper proposes applying dynamic, heterogeneity aware, load balancing techniques within CFD simulations. nSharma, a software package that fully integrates with OpenFOAM, is presented and assessed. Performance gains are demonstrated, achieved by reducing busy times standard deviation among resources, i.e. heterogeneous computing resources are kept busy with useful work due to an effective workload distribution. To best of authors' knowledge, nSharma is the first implementation and integration of heterogeneity aware load balancing in OpenFOAM and will be made publicly available in order to foster its adoption by the large community of OpenFOAM users.

Computational Efficiency Assessment of Adaptive Mesh Refinement for Turbulent Jets in Crossflow

“…Load balanced AMR introduced by Rettenmaier et al [2] improved current AMR capabilities by extending the AMR to axisymmetric cases, adding multi-criteria refinement and additionally included native load balancing. The paper by Ribeiro et al [13] presented a dynamic load balancing technique, which aims to efficiently redistribute the workload based on system heterogeneity and overall use. Performance gains of up to 38% have been noted.…”