A call to arms for task parallelism in multi‐scale materials modeling |
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| Authors: | Nathan R. Barton Joel V. Bernier Jaroslaw Knap Anne J. Sunwoo Ellen K. Cerreta Todd J. Turner |
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| Affiliation: | 1. Lawrence Livermore National Laboratory, Livermore, CA 94550, U.S.A.;2. U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005, U.S.A.;3. Los Alamos National Laboratory, Los Alamos, NM 87545, U.S.A.;4. U.S. Air Force Research Laboratory, Wright Patterson AFB, OH 45433, U.S.A. |
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| Abstract: | Simulations based on multi‐scale material models enabled by adaptive sampling have demonstrated speedup factors exceeding an order of magnitude. The use of these methods in parallel computing is hampered by dynamic load imbalance, with load imbalance measurably reducing the achieved speedup. Here we discuss these issues in the context of task parallelism, showing results achieved to date and discussing possibilities for further improvement. In some cases, the task parallelism methods employed to date are able to restore much of the potential wall‐clock speedup. The specific application highlighted here focuses on the connection between microstructure and material performance using a polycrystal plasticity‐based multi‐scale method. However, the parallel load balancing issues are germane to a broad class of multi‐scale problems. Copyright © 2011 John Wiley & Sons, Ltd. |
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| Keywords: | solids materials science multiscale plasticity parallelization finite element methods |
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