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A Parallel Particle Tracking Framework for Applications in Scientific Computing

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Abstract

Particle tracking methods are a versatile computational technique central to the simulation of a wide range of scientific applications. In this paper, we present a new parallel particle tracking framework for the applications of scientific computing. The framework includes the “in-element” particle tracking method, which is based on the assumption that particle trajectories are computed by problem data localized to individual elements, as well as the dynamic partitioning of particle-mesh computational systems. The ultimate goal of this research is to develop a parallel in-element particle tracking framework capable of interfacing with a different order of accuracy of ordinary differential equation (ODE) solver. The parallel efficiency of such particle-mesh systems depends on the partitioning of both the mesh elements and the particles; this distribution can change dramatically because of movement of the particles and adaptive refinement of the mesh. To address this problem we introduce a combined load function that is a function of both the particle and mesh element distributions. We present experimental results that detail the performance of this parallel load balancing approach for a three-dimensional particle-mesh test problem on an unstructured, adaptive mesh, and demonstrate the ability of interfacing with different ODE solvers.

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Authors and Affiliations

  1. Major Shared Resource Center (MSRC), U.S. Army Engineer Research and Development Center (ERDC), Vicksburg, MS, 39180-6199, USA

    Jing-Ru C. Cheng

  2. Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA

    Paul E. Plassmann

Authors
  1. Jing-Ru C. Cheng
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  2. Paul E. Plassmann
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Cheng, JR.C., Plassmann, P.E. A Parallel Particle Tracking Framework for Applications in Scientific Computing. The Journal of Supercomputing 28, 149–164 (2004). https://doi.org/10.1023/B:SUPE.0000020175.26125.c1

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  • DOI: https://doi.org/10.1023/B:SUPE.0000020175.26125.c1

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