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Vectorization techniques for efficient agent-based model simulations of tumor growth

Jan Poleszczuk, Heiko Enderling
doi: https://doi.org/10.1101/032086
Jan Poleszczuk
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Heiko Enderling
Roles: ICBP Member
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Abstract

Multi-scale agent-based models are increasingly used to simulate tumor growth dynamics. Simulating such complex systems is often a great challenge despite large computational power of modern computers and, thus, implementation techniques are becoming as important as the models themselves. Here we show, using a simple agent-based model of tumor growth, how the computational time required for simulation can be decreased by using vectorization techniques. In numerical examples we observed up to 30-fold increases in computation performance when standard approaches were, at least in part, replaced with vectorized routines in MATLAB.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 17, 2015.
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Vectorization techniques for efficient agent-based model simulations of tumor growth
Jan Poleszczuk, Heiko Enderling
bioRxiv 032086; doi: https://doi.org/10.1101/032086
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Vectorization techniques for efficient agent-based model simulations of tumor growth
Jan Poleszczuk, Heiko Enderling
bioRxiv 032086; doi: https://doi.org/10.1101/032086

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