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Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors

Falk, M. and Ott, M. and Ertl, T. and Klann, M. and Koeppl, H. (2011):
Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors.
In: CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology, New York, New York, USA, ACM Press, [Online-Edition: http://dl.acm.org/citation.cfm?doid=2037509.2037521],
[Conference or Workshop Item]

Abstract

The complexity of biological systems is enormous, even when considering a single cell where a multitude of highly par- allel and intertwined processes take place on the molec- ular level. This paper focuses on the parallel simulation of signal transduction processes within a cell carried out solely on the graphics processing unit (GPU). Each signaling molecule is represented by an agent performing a discrete- time continuous-space random walk to model its di usion through the cell. Since the interactions and reactions be- tween the agents can be competitive and are interdependent, we propose spatial partitioning for the reaction detection to overcome the data dependencies in the parallel execution of reactions. In addition, we present a simple way to simulate the Michaelis-Menten kinetics in our particle-based method using a per-particle delay. We apply this agent-based simu- lation to model signal transduction in the MAPK (Mitogen- Activated Protein Kinase) cascade both with and without cytoskeletal laments. Finally, we compare the speed-up of our GPU simulation with a parallelized CPU version result- ing in a twelvefold speedup.

Item Type: Conference or Workshop Item
Erschienen: 2011
Creators: Falk, M. and Ott, M. and Ertl, T. and Klann, M. and Koeppl, H.
Title: Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors
Language: English
Abstract:

The complexity of biological systems is enormous, even when considering a single cell where a multitude of highly par- allel and intertwined processes take place on the molec- ular level. This paper focuses on the parallel simulation of signal transduction processes within a cell carried out solely on the graphics processing unit (GPU). Each signaling molecule is represented by an agent performing a discrete- time continuous-space random walk to model its di usion through the cell. Since the interactions and reactions be- tween the agents can be competitive and are interdependent, we propose spatial partitioning for the reaction detection to overcome the data dependencies in the parallel execution of reactions. In addition, we present a simple way to simulate the Michaelis-Menten kinetics in our particle-based method using a per-particle delay. We apply this agent-based simu- lation to model signal transduction in the MAPK (Mitogen- Activated Protein Kinase) cascade both with and without cytoskeletal laments. Finally, we compare the speed-up of our GPU simulation with a parallelized CPU version result- ing in a twelvefold speedup.

Title of Book: CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology
Place of Publication: New York, New York, USA
Publisher: ACM Press
Uncontrolled Keywords: agent-based simulation,gpu acceleration,mapk,systems biology
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Date Deposited: 04 Apr 2014 14:14
Official URL: http://dl.acm.org/citation.cfm?doid=2037509.2037521
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