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Extreme-Scale AMR

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7 Author(s)
Burstedde, C. ; Inst. for Comput. Eng. & Sci., Univ. of Texas at Austin, Austin, TX, USA ; Ghattas, O. ; Gurnis, M. ; Isaac, T.
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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.

Published in:

High Performance Computing, Networking, Storage and Analysis (SC), 2010 International Conference for

Date of Conference:

13-19 Nov. 2010

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