Abstract
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× 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.
| Original language | English |
|---|---|
| Pages (from-to) | 210-220 |
| Number of pages | 11 |
| Journal | Computers and Geosciences |
| Volume | 72 |
| DOIs | |
| Publication status | Published - Nov 2014 |
Keywords
- Computing
- Gauss-Seidel
- GPGPU
- Ice-flow modelling
- Surface process modelling
Programme Area
- Programme Area 5: Nature and Climate
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