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Computing, Networking, Storage and Analysis
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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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