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

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.
 [1] ;  [2] ;  [1] ;  [3] ;  [1]
  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:
Grant/Contract Number:
SC0013919; SC00066117
Accepted Manuscript
Journal Name:
SIAM Journal on Scientific Computing
Additional Journal Information:
Journal Volume: 40; Journal Issue: 1; Journal ID: ISSN 1064-8275
Research Org:
Argonne National Laboratory (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) (SC-21); Rensselaer Polytechnic Inst., Troy, NY (United States); Simmetrix Inc., Clifton Park, NY (United States)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; partition improvement; graph/hypergraph; unstructured mesh; dynamic load balancing
OSTI Identifier: