An optimization approach for agent-based computational models of biological development

1Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

Current research in the field of computational biology often involves simulations on high-performance computer clusters. It is crucial that the code of such simulations is efficient and correctly reflects the model specifications. In this paper, we present an optimization strategy for agent-based simulations of biological dynamics using Intel Xeon Phi coprocessors, demonstrated by a prize-winning entry of the “Intel Modern Code Developer Challenge” competition. These optimizations allow simulating various biological mechanisms, in particular the simulation of millions of cells, their proliferation, movements and interactions in 3D space. Overall, our results demonstrate a powerful approach to implement and conduct very detailed and large-scale computational simulations for biological research. We also highlight the main difficulties faced when developing such optimizations, in particular the assessment of the simulation accuracy, the dependencies between different optimization techniques and counter-intuitive effects in the speed of the optimized solution. The overall speedup of 595 × shows a good parallel scalability.

Cite

CITATION STYLE

APA

Gonzalez-de-Aledo, P., Vladimirov, A., Manca, M., Baugh, J., Asai, R., Kaiser, M., & Bauer, R. (2018). An optimization approach for agent-based computational models of biological development. Advances in Engineering Software, 121, 262–275. https://doi.org/10.1016/j.advengsoft.2018.03.010

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free