CellGPU  0.8.0
GPU-accelerated simulations of cells

CellGPU implements GPU-accelerated algorithms to simulate off-lattice models of cells. Its current two main feature sets focus on a Voronoi-decomposition-based model of two-dimensional monolayers and on a two-dimensional dynamical version of the vertex model. CellGPU grew out of DMS' "DelGPU" and "VoroGuppy" projects, and the current class structure still bears some traces of that (please see the contributing page of the documentation, which is maintained at https://dmsussman.gitlab.io/cellGPUdocumentation for information on upcoming code refactoring and new planned features). The paper describing this code in more detail can currently be found on the arXiv (https://arxiv.org/abs/1702.02939), or in print ( http://www.sciencedirect.com/science/article/pii/S0010465517301832)

Information on installing the project and contributing to it is contained in the relevant markdown files in the base directory and in the doc/markdown directory. Documentation of the code is maintained via Doxygen, which can be viewed at the gitlab.io pagea linked to above, or by compiling the doxygen documentation in the "/doc" directory

A very rough outline of some of the main classes and the basic operating flow of the primary branches of the code can be found here; this page is a good place to start before diving into the code (Please note that if you are reading this on the Gitlab main page the links will not work... visit the main documentation page at https://dmsussman.gitlab.io/cellGPUdocumentation or compile Doxygen documentation locally).

By default cellGPU includes a few different classes, mostly using the netCDF format, for saving simulation data. For convenience, a few Mathematica scripts demonstrating how to load these files and turn them into simple visualizations are included in the visualizationTools directory – these should be readily portable to matlab, python, etc.

Project information

Here are some convenient links to a variety of general information about the cellGPU project; all of the below can also be accessed from the Project information tab (links work on the gitlab.io documenation website)

Basic class overview

Installation guide

Sample code snippets

Contributing to cellGPU


Open-source information

cellGPU version information