Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures

Solving large sparse linear systems is a time-consuming step in basin modeling or reservoir simulation. The choice of a robust preconditioner strongly impact the performance of the overall simulation. Heterogeneous architectures based on General Purpose computing on Graphic Processing Units (GPGPU)...

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Main Authors: Roussel Adrien, Gratien Jean-Marc, Gautier Thierry
Format: Article
Language:English
Published: EDP Sciences 2016-11-01
Series:Oil & Gas Science and Technology
Online Access:https://doi.org/10.2516/ogst/2016020
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spelling doaj-23fac2c7a0a94c748b6473343d8bed202021-02-02T01:54:55ZengEDP SciencesOil & Gas Science and Technology1294-44751953-81892016-11-017166510.2516/ogst/2016020ogst150225Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous ArchitecturesRoussel AdrienGratien Jean-MarcGautier ThierrySolving large sparse linear systems is a time-consuming step in basin modeling or reservoir simulation. The choice of a robust preconditioner strongly impact the performance of the overall simulation. Heterogeneous architectures based on General Purpose computing on Graphic Processing Units (GPGPU) or many-core architectures introduce programming challenges which can be managed in a transparent way for developer with the use of runtime systems. Nevertheless, algorithms need to be well suited for these massively parallel architectures. In this paper, we present preconditioning techniques which enable to take advantage of emerging architectures. We also present our task-based implementations through the use of the HARTS (Heterogeneous Abstract RunTime System) runtime system, which aims to manage the recent architectures. We focus on two preconditoners. The first is ILU(0) preconditioner implemented on distributing memory systems. The second one is a multi-level domain decomposition method implemented on a shared-memory system. Obtained results are then presented on corresponding architectures, which open the way to discuss on the scalability of such methods according to numerical performances while keeping in mind that the next step is to propose a massively parallel implementations of these techniques.https://doi.org/10.2516/ogst/2016020
collection DOAJ
language English
format Article
sources DOAJ
author Roussel Adrien
Gratien Jean-Marc
Gautier Thierry
spellingShingle Roussel Adrien
Gratien Jean-Marc
Gautier Thierry
Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
Oil & Gas Science and Technology
author_facet Roussel Adrien
Gratien Jean-Marc
Gautier Thierry
author_sort Roussel Adrien
title Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
title_short Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
title_full Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
title_fullStr Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
title_full_unstemmed Using Runtime Systems Tools to Implement Efficient Preconditioners for Heterogeneous Architectures
title_sort using runtime systems tools to implement efficient preconditioners for heterogeneous architectures
publisher EDP Sciences
series Oil & Gas Science and Technology
issn 1294-4475
1953-8189
publishDate 2016-11-01
description Solving large sparse linear systems is a time-consuming step in basin modeling or reservoir simulation. The choice of a robust preconditioner strongly impact the performance of the overall simulation. Heterogeneous architectures based on General Purpose computing on Graphic Processing Units (GPGPU) or many-core architectures introduce programming challenges which can be managed in a transparent way for developer with the use of runtime systems. Nevertheless, algorithms need to be well suited for these massively parallel architectures. In this paper, we present preconditioning techniques which enable to take advantage of emerging architectures. We also present our task-based implementations through the use of the HARTS (Heterogeneous Abstract RunTime System) runtime system, which aims to manage the recent architectures. We focus on two preconditoners. The first is ILU(0) preconditioner implemented on distributing memory systems. The second one is a multi-level domain decomposition method implemented on a shared-memory system. Obtained results are then presented on corresponding architectures, which open the way to discuss on the scalability of such methods according to numerical performances while keeping in mind that the next step is to propose a massively parallel implementations of these techniques.
url https://doi.org/10.2516/ogst/2016020
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