Burstedde, Carsten and Ghattas, Omar and Gurnis, Michael and Isaac, Tobin and Stadler, Georg and Warburton, Tim and Wilcox, Lucas C. (2010) Extreme-Scale AMR. In: 2010 International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE , Piscataway, NJ, pp. 1-12. ISBN 978-1-4244-7557-5. https://resolver.caltech.edu/CaltechAUTHORS:20121119-100717889
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Abstract
Many problems are characterized by dynamics occurring on a wide range of length and time scales. One approach to overcoming the tyranny of scales is adaptive mesh refinement/coarsening (AMR), which dynamically adapts the mesh to resolve features of interest. However, the benefits of AMR are difficult to achieve in practice, particularly on the petascale computers that are essential for difficult problems. Due to the complex dynamic data structures and frequent load balancing, scaling dynamic AMR to hundreds of thousands of cores has long been considered a challenge. Another difficulty is extending parallel AMR techniques to high-order-accurate, complex-geometry-respecting methods that are favored for many classes of problems. Here we present new parallel algorithms for parallel dynamic AMR on forest-ofoctrees geometries with arbitrary-order continuous and discontinuous finite/spectral element discretizations. The implementations of these algorithms exhibit excellent weak and strong scaling to over 224,000 Cray XT5 cores for multiscale geophysics problems.
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Additional Information: | © 2010 IEEE. Date of Current Version: 29 November 2010; Issue Date: 13-19 November 2010. This work was partially supported by NSF (OCI-0749334, OCI-0748898, CCF-0427985, DMS-0724746, OPP-0941678), AFOSR (FA9550-09-1-0608), and DOE (06ER25782, 08ER25860, 08NA28615, SC0002710). We thank Laura Alisic, George Biros, Martin Burtscher, Rahul Sampath, and Tiankai Tu for extended discussions. We also thank TACC for providing access to Ranger under TeraGrid award MCA04N026, and the NCCS/ORNL for early-user access to Jaguar. | ||||||||||||||||||||||
Group: | Seismological Laboratory | ||||||||||||||||||||||
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DOI: | 10.1109/SC.2010.25 | ||||||||||||||||||||||
Record Number: | CaltechAUTHORS:20121119-100717889 | ||||||||||||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20121119-100717889 | ||||||||||||||||||||||
Official Citation: | Burstedde, C.; Ghattas, O.; Gurnis, M.; Isaac, T.; Stadler, G.; Warburton, T.; Wilcox, L.; , "Extreme-Scale AMR," High Performance Computing, Networking, Storage and Analysis (SC), 2010 International Conference for , vol., no., pp.1-12, 13-19 Nov. 2010 doi: 10.1109/SC.2010.25 | ||||||||||||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||||||
ID Code: | 35534 | ||||||||||||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||||||||||||
Deposited By: | INVALID USER | ||||||||||||||||||||||
Deposited On: | 19 Nov 2012 19:35 | ||||||||||||||||||||||
Last Modified: | 09 Nov 2021 23:16 |
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