Journal
COMPUTERS & GEOSCIENCES
Volume 72, Issue -, Pages 210-220Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cageo.2014.07.019
Keywords
Ice-flow modelling; Computing; GPGPU; Gauss-Seidel; Surface process modelling
Funding
- Danish Council for Independent Research under the Sapere Aude program
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Studies of glaciers and ice sheets have increased the demand for high performance numerical ice flow models over the past decades. When exploring the highly non-linear dynamics of fast flowing glaciers and ice streams, or when coupling multiple flow processes for ice, water, and sediment, researchers are often forced to use super-computing clusters. As an alternative to conventional high-performance computing hardware, the Graphical Processing Unit (GPU) is capable of massively parallel computing while retaining a compact design and low cost. In this study, we present a strategy for accelerating a higher-order ice flow model using a GPU. By applying the newest GPU hardware, we achieve up to 180 x speedup compared to a similar but serial CPU implementation. Our results suggest that GPU acceleration is a competitive option for ice-flow modelling when compared to CPU-optimised algorithms parallelised by the OpenMP or Message Passing Interface (MPI) protocols. (C) 2014 Elsevier Ltd. All rights reserved.
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