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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Online Access: | https://doi.org/10.2516/ogst/2016020 |
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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 |
work_keys_str_mv |
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