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Accelerating a fluvial incision and landscape evolution model with parallelism

Author:
Barnes, Richard
Source:
Geomorphology 2019 v.330 pp. 28-39
ISSN:
0169-555X
Subject:
algorithms, landscapes, models
Abstract:
Solving inverse problems, performing sensitivity analyses, and achieving statistical rigour in landscape evolution models require running many model realizations. Parallel computation is necessary to achieve this in a reasonable time. However, no previous landscape evolution algorithm is able to leverage modern parallelism. Here, I describe an algorithm that can utilize the parallel potential of GPUs and many-core processors, in addition to working well in serial. The new algorithm runs 43× faster (70 s vs. 3000 s on a 10,000×10,000 input) than the previous state-of-the-art and exhibits sublinear scaling with input size. I also identify key techniques for multiple flow direction routing and quickly eliminating landscape depressions and local minima. Complete, well-commented, easily adaptable source code for all versions of the algorithm is available on Github and Zenodo.
Agid:
6283960