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SCHEDULE: NOV 15-20, 2015
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Geometric-Aware Partitioning on Large-Scale Data for Parallel Quad Meshing
SESSION: Regular & ACM Student Research Competition Poster Reception
EVENT TYPE: Posters, Receptions, ACM Student Research Competition
EVENT TAG(S): HPC Beginner Friendly, Regular Poster
TIME: 5:15PM - 7:00PM
SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold
AUTHOR(S):Wuyi Yu, Qin Chen, Jian Tao, Xin Li
ROOM:Level 4 - Lobby
ABSTRACT:
We present a partitioning algorithm to decompose complex 2D data into small simple subregions for effective parallel quad meshing. We formulate the partitioning problem for effective parallel quad meshing, which leads to an expensive quadratic integer optimization problem with linear constraints. Directly solving this problem is prohibitive for large-scale data partitioning. Hence, we suggest a more efficient two-step algorithm to obtain an approximate solution. First, we partition the region into a set of square-like cells using L_infity Centroidal Voronoi Tessellation (CVT), then we solve a graph partitioning on the dual graph of this CVT to minimize the total boundary length of the partitioning, while enforcing the load balancing and each subregion’s connectivity. With this geometry-aware decomposition, subregions are distributed to multiple processors for parallel quadrilateral mesh generation.
Chair/Author Details:
Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|
Wuyi Yu - Louisiana State University
Qin Chen - Louisiana State University
Jian Tao - Louisiana State University
Xin Li - Louisiana State University
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