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Title: Improving Unstructured Mesh Partitions for Multiple Criteria Using Mesh Adjacencies

Abstract

The scalability of unstructured mesh based applications depends on partitioning methods that quickly balance the computational work while reducing communication costs. Zhou et al. [SIAM J. Sci. Comput., 32 (2010), pp. 3201{3227; J. Supercomput., 59 (2012), pp. 1218{1228] demonstrated the combination of (hyper)graph methods with vertex and element partition improvement for PHASTA CFD scaling to hundreds of thousands of processes. Our work generalizes partition improvement to support balancing combinations of all the mesh entity dimensions (vertices, edges, faces, regions) in partitions with imbalances exceeding 70%. Improvement results are then presented for multiple entity dimensions on up to one million processes on meshes with over 12 billion tetrahedral elements.

Authors:
 [1];  [2];  [1];  [3];  [1]
+ Show Author Affiliations
  1. Rensselaer Polytechnic Inst., Troy, NY (United States). Scientific Computation Research Center (SCOREC)
  2. Univ. of Colorado, Boulder, CO (United States); Cenaero, Gosselies (Belgium)
  3. Univ. of Colorado, Boulder, CO (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States). Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); Rensselaer Polytechnic Inst., Troy, NY (United States); Simmetrix Inc., Clifton Park, NY (United States)
OSTI Identifier:
1438033
Grant/Contract Number:  
SC0013919; SC00066117
Resource Type:
Accepted Manuscript
Journal Name:
SIAM Journal on Scientific Computing
Additional Journal Information:
Journal Volume: 40; Journal Issue: 1; Journal ID: ISSN 1064-8275
Publisher:
SIAM
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; partition improvement; graph/hypergraph; unstructured mesh; dynamic load balancing

Citation Formats

Smith, Cameron W., Rasquin, Michel, Ibanez, Dan, Jansen, Kenneth E., and Shephard, Mark S. Improving Unstructured Mesh Partitions for Multiple Criteria Using Mesh Adjacencies. United States: N. p., 2018. Web. doi:10.1137/15M1027814.
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Smith, Cameron W., Rasquin, Michel, Ibanez, Dan, Jansen, Kenneth E., & Shephard, Mark S. Improving Unstructured Mesh Partitions for Multiple Criteria Using Mesh Adjacencies. United States. https://doi.org/10.1137/15M1027814
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Smith, Cameron W., Rasquin, Michel, Ibanez, Dan, Jansen, Kenneth E., and Shephard, Mark S. Tue . "Improving Unstructured Mesh Partitions for Multiple Criteria Using Mesh Adjacencies". United States. https://doi.org/10.1137/15M1027814. https://www.osti.gov/servlets/purl/1438033.
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@article{osti_1438033,
title = {Improving Unstructured Mesh Partitions for Multiple Criteria Using Mesh Adjacencies},
author = {Smith, Cameron W. and Rasquin, Michel and Ibanez, Dan and Jansen, Kenneth E. and Shephard, Mark S.},
abstractNote = {The scalability of unstructured mesh based applications depends on partitioning methods that quickly balance the computational work while reducing communication costs. Zhou et al. [SIAM J. Sci. Comput., 32 (2010), pp. 3201{3227; J. Supercomput., 59 (2012), pp. 1218{1228] demonstrated the combination of (hyper)graph methods with vertex and element partition improvement for PHASTA CFD scaling to hundreds of thousands of processes. Our work generalizes partition improvement to support balancing combinations of all the mesh entity dimensions (vertices, edges, faces, regions) in partitions with imbalances exceeding 70%. Improvement results are then presented for multiple entity dimensions on up to one million processes on meshes with over 12 billion tetrahedral elements.},
doi = {10.1137/15M1027814},
journal = {SIAM Journal on Scientific Computing},
number = 1,
volume = 40,
place = {United States},
year = {2018},
month = {2}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1137/15M1027814
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Cited by: 7 works
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Figures / Tables:

Fig. 1 Fig. 1: (left) Example of a mesh, (middle) its partition model, and (right) its ownership. Discs and bold segments denote entity ownership.
All figures and tables (23 total)
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    Works referencing / citing this record:

    In-memory integration of existing software components for parallel adaptive unstructured mesh workflows: In-memory integration of existing software components for parallel adaptive unstructured mesh workflows
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    Interface Tracking Investigation of Geometric Effects on the Bubbly Flow in PWR Subchannels
    journal, August 2018

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      Figures / Tables found in this record:

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