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nSharma: Numerical Simulation Heterogeneity Aware Runtime Manager for OpenFOAM
CFD simulations are a fundamental engineering application,implying huge workloads, often with dynamic behaviour due to run-time mesh refinement. Parallel processing over heterogeneous distributedmemory clusters is often used to process such workloads. The executionof dynamic workloads over a set of heterogeneous resources leads to loadimbalances that severely impacts execution time, when static uniformload distribution is used. This paper proposes applying dynamic, het-erogeneity aware, load balancing techniques within CFD simulations.nSharma, a software package that fully integrates with OpenFOAM, ispresented and assessed. Performance gains are demonstrated, achievedby reducing busy times standard deviation among resources, i.e. hetero-geneous computing resources are kept busy with useful work due to aneffective workload distribution. To best of authors’ knowledge, nSharmais the first implementation and integration of heterogeneity aware loadbalancing in OpenFOAM and will be made publicly available in order tofoster its adoption by the large community of OpenFOAM users. ; The authors would like to thank the financial funding by FEDER through the COMPETE 2020 Program, the National Funds through FCT under the projects UID/CTM/50025/2013. The first author was partially funded by the PT-FLAD Chair on Smart Cities & Smart Governance and also by the School of Engineering, University of Minho within project Performance Portability on Scalable Heterogeneous Computing Systems. The authors also wish to thank Kyle Mooney for making available his code supporting migration of dynamically refined meshes, as well as acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources.
nSharma: Numerical Simulation Heterogeneity Aware Runtime Manager for OpenFOAM
CFD simulations are a fundamental engineering application,implying huge workloads, often with dynamic behaviour due to run-time mesh refinement. Parallel processing over heterogeneous distributedmemory clusters is often used to process such workloads. The executionof dynamic workloads over a set of heterogeneous resources leads to loadimbalances that severely impacts execution time, when static uniformload distribution is used. This paper proposes applying dynamic, het-erogeneity aware, load balancing techniques within CFD simulations.nSharma, a software package that fully integrates with OpenFOAM, ispresented and assessed. Performance gains are demonstrated, achievedby reducing busy times standard deviation among resources, i.e. hetero-geneous computing resources are kept busy with useful work due to aneffective workload distribution. To best of authors’ knowledge, nSharmais the first implementation and integration of heterogeneity aware loadbalancing in OpenFOAM and will be made publicly available in order tofoster its adoption by the large community of OpenFOAM users. ; The authors would like to thank the financial funding by FEDER through the COMPETE 2020 Program, the National Funds through FCT under the projects UID/CTM/50025/2013. The first author was partially funded by the PT-FLAD Chair on Smart Cities & Smart Governance and also by the School of Engineering, University of Minho within project Performance Portability on Scalable Heterogeneous Computing Systems. The authors also wish to thank Kyle Mooney for making available his code supporting migration of dynamically refined meshes, as well as acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources.
nSharma: Numerical Simulation Heterogeneity Aware Runtime Manager for OpenFOAM
Ribeiro, Roberto (Autor:in) / Santos, Luís Paulo (Autor:in) / Nóbrega, J. M. (Autor:in)
01.01.2018
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DDC:
690
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