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Abstract-As our expectations of what computer systems can do and our ability to capture data improves, the desire to perform ever more computationally intensive tasks increases. Often these tasks, comprising vast numbers of repeated computations, are highly interdependent on each other -a closely coupled problem. The process of Landscape-Evolution Modelling is an example of such a problem. In order to produce realistic models it is necessary to process landscapes containing millions of data points over time periods extending up to millions of years. This leads to non-tractable execution times, often in the order of years. Researchers therefore seek multiple orders of magnitude reduction in the execution time of these models. The massively parallel programming environment offered through General Purpose Graphical Processing Units offers the potential for multiple orders of magnitude speedup in code execution times.In this paper we demonstrate how the time dominant parts of a Landscape-Evolution Model can be recoded for a massively parallel architecture providing two orders of magnitude reduction in execution time.