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2018 | OriginalPaper | Buchkapitel

Viscoelastic Crustal Deformation Computation Method with Reduced Random Memory Accesses for GPU-Based Computers

verfasst von : Takuma Yamaguchi, Kohei Fujita, Tsuyoshi Ichimura, Anne Glerum, Ylona van Dinther, Takane Hori, Olaf Schenk, Muneo Hori, Lalith Wijerathne

Erschienen in: Computational Science – ICCS 2018

Verlag: Springer International Publishing

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Abstract

The computation of crustal deformation following a given fault slip is important for understanding earthquake generation processes and reduction of damage. In crustal deformation analysis, reflecting the complex geometry and material heterogeneity of the crust is important, and use of large-scale unstructured finite-element method is suitable. However, since the computation area is large, its computation cost has been a bottleneck. In this study, we develop a fast unstructured finite-element solver for GPU-based large-scale computers. By computing several times steps together, we reduce random access, together with the use of predictors suitable for viscoelastic analysis to reduce the total computational cost. The developed solver enabled 2.79 times speedup from the conventional solver. We show an application example of the developed method through a viscoelastic deformation analysis of the Eastern Mediterranean crust and mantle following a hypothetical M 9 earthquake in Greece by using a 2,403,562,056 degree-of-freedom finite-element model.

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Fußnoten
1
Piz Daint comprises of 1,431 \(\times \) multicore compute node (Two Intel Xeon E5-2695 v4) and 5,320 \(\times \) hybrid compute node (Intel Xeon E5-2690 v3 + NVIDIA Tesla P100) connected by Cray Aries routing and communications ASIC, and Dragonfly network topology.
 
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Metadaten
Titel
Viscoelastic Crustal Deformation Computation Method with Reduced Random Memory Accesses for GPU-Based Computers
verfasst von
Takuma Yamaguchi
Kohei Fujita
Tsuyoshi Ichimura
Anne Glerum
Ylona van Dinther
Takane Hori
Olaf Schenk
Muneo Hori
Lalith Wijerathne
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-93701-4_3

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