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Performance Evaluation of a Parallel Algorithm for Simultaneous Untangling and Smoothing of Tetrahedral Meshes

Benitez, Domingo, Eduardo Rodriguez, Jose Maria Escobar, and Rafael Montenegro

22nd International Meshing Roundtable, Springer-Verlag, pp.579-598, October 13-16 2013


22nd International Meshing Roundtable
Orlando, FL
October 13-16,2013

Departamento de Informatica y Sistemas, University of Las Palmas de Gran Canaria, Spain
University Institute for Intelligent Systems and Numerical Applications in Engineering, SIANI, University of Las Palmas de Gran Canaria, Spain
Email: {dbenitez,erodriguez,jmescobar,rmontenegro}

A new parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. We provide a detailed analysis of its performance on shared-memory many-core computer architectures. This performance analysis includes the evaluation of execution time, parallel scalability, load balancing, and parallelism bottlenecks. Additionally, we compare the impact of three previously published graph coloring procedures on the performance of our parallel algorithm. We use six benchmark meshes with a wide range of sizes. Using these experimental data sets, we describe the behavior of the parallel algorithm for different data sizes. We demonstrate that this algorithm is highly scalable when it runs on two different high-performance many-core computers with up to 128 processors. However, some parallel deterioration is observed. Here, we analyze the main causes of this parallel deterioration.

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