Abstract
A parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. This algorithm is derived from a sequential mesh optimization method. We provide a detailed analysis of its parallel scalability and efficiency, load balancing, and parallelism bottlenecks using six benchmark meshes. In addition, the influence of three previously-published graph coloring techniques on the performance of our parallel algorithm is evaluated. We demonstrate that the proposed algorithm is highly scalable when run on a shared-memory computer with up to 128 Itanium 2 processors. However, some parallel deterioration is observed. Here, we analyze its main causes using a theoretical performance model and experimental results.
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Acknowledgments
This work has been supported by the Spanish Sec. Estado Univ. e Inv., Min. Economa y Competitividad and FEDER, contract: CGL2011-29396-C03-01. It has been also supported by Fondo Sec. CONACYT SENER Hidrocarburos, contract: 163723, and two CESGA ICTS projects.
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Benitez, D., Rodríguez, E., Escobar, J.M., Montenegro, R. (2014). The Effect of Parallelization on a Tetrahedral Mesh Optimization Method. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2013. Lecture Notes in Computer Science(), vol 8385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55195-6_15
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DOI: https://doi.org/10.1007/978-3-642-55195-6_15
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