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Preliminary Work on Data-Parallel Execution of Cellular Potts Models

The Cellular Potts Model (CPM) is a very important algorithm in systems biology to simulate cell sorting and the formation of organ structures. However its computational intensity has limited the size and scope of its applicability. Parallel computing techniques using traditional cluster computing have been marginally successful in addressing scalability of CPMs. In this paper, we explore data-parallel computing architectures such as graphics processing units (GPUs) for simulating large-scale CPMs. Our preliminary results indicate that our techniques running on a single desktop are up to 30x faster than previous methods executing on computing clusters consisting of upto 25 nodes.