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Title: Advances in Patch-Based Adaptive Mesh Refinement Scalability

Abstract

Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extension of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.

Authors:
 [1];  [1]
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  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1241965
Report Number(s):
LLNL-JRNL-668377
Journal ID: ISSN 0743-7315
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Parallel and Distributed Computing
Additional Journal Information:
Journal Volume: 89; Journal ID: ISSN 0743-7315
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Gunney, Brian T.N., and Anderson, Robert W. Advances in Patch-Based Adaptive Mesh Refinement Scalability. United States: N. p., 2015. Web. doi:10.1016/j.jpdc.2015.11.005.
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Gunney, Brian T.N., & Anderson, Robert W. Advances in Patch-Based Adaptive Mesh Refinement Scalability. United States. https://doi.org/10.1016/j.jpdc.2015.11.005
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Gunney, Brian T.N., and Anderson, Robert W. Fri . "Advances in Patch-Based Adaptive Mesh Refinement Scalability". United States. https://doi.org/10.1016/j.jpdc.2015.11.005. https://www.osti.gov/servlets/purl/1241965.
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@article{osti_1241965,
title = {Advances in Patch-Based Adaptive Mesh Refinement Scalability},
author = {Gunney, Brian T.N. and Anderson, Robert W.},
abstractNote = {Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extension of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.},
doi = {10.1016/j.jpdc.2015.11.005},
journal = {Journal of Parallel and Distributed Computing},
number = ,
volume = 89,
place = {United States},
year = {Fri Dec 18 00:00:00 EST 2015},
month = {Fri Dec 18 00:00:00 EST 2015}
}
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https://doi.org/10.1016/j.jpdc.2015.11.005
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Works referenced in this record:

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