AMR-based molecular dynamics for non-uniform, highly dynamic particle simulations
| Autor: | Olivier Durand, Raphaël Prat, Laurent Soulard, Raymond Namyst, Laurent Colombet, Thierry Carrard |
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| Přispěvatelé: | Commissariat à l'énergie atomique et aux énergies alternatives (CEA), DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), This work was funded by the French Programme d’Investissements d’Avenir (PIA) project SMICE, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Adaptive mesh refinement
Computer science business.industry Computation General Physics and Astronomy Cloud computing Data structure 01 natural sciences Atomic units 010305 fluids & plasmas Computational science Molecular dynamics Hardware and Architecture 0103 physical sciences [INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] 010306 general physics business Massively parallel Xeon Phi |
| Zdroj: | Computer Physics Communications Computer Physics Communications, 2020, 253, pp.107177. ⟨10.1016/j.cpc.2020.107177⟩ Computer Physics Communications, Elsevier, 2020, 253, pp.107177. ⟨10.1016/j.cpc.2020.107177⟩ |
| ISSN: | 0010-4655 |
| Popis: | International audience; Accurate simulations of metal under heavy shocks, leading to fragmentation and ejection of particles, cannot be achieved by simply hydrodynamic models and require to be performed at atomic scale using molecular dynamics methods. In order to cope with billions of particles exposed to short range interactions, such molecular dynamics methods need to be highly optimized over massively parallel supercomputers. In this paper, we propose to leverage Adaptive Mesh Refinement techniques to improve efficiency of molecular dynamics code on highly heterogeneous particle configurations. We introduce a series of techniques that optimize the force computation loop using multi-threading and vectorization-friendly data structures. Our design is guided by the need for load balancing and adaptivity raised by highly dynamic particle sets. We analyze performance results on several simulation scenarios, such as the production of an ejecta cloud from shock-loaded metallic surfaces, using a large number of nodes equipped by Intel Xeon Phi Knights Landing processors. Performance obtained with our new Molecular Dynamics code achieves speedups greater than 1.38 against the state-of-the-art LAMMPS implementation. |
| Databáze: | OpenAIRE |
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