celIGPU: Massively parallel simulations of dynamic vertex models
DM Sussman, COMPUTER PHYSICS COMMUNICATIONS, 219, 400-406 (2017).
Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular- dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. celIGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running celIGPU entirely on the CPU versus its performance when running on a range of commercial and server grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, celIGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program summary Program Title: celIGPU Program Files doi: http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off- lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/celIGPUdocumentation (C) 2017 Elsevier B.V. All rights reserved.
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