Falk, M. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H. (2011)
Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors.
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. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H. |
| Type of entry: | Bibliographie |
| Title: | Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors |
| Language: | English |
| Date: | 2011 |
| Place of Publication: | New York, New York, USA |
| Publisher: | ACM Press |
| Book Title: | CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology |
| URL / URN: | http://dl.acm.org/citation.cfm?doid=2037509.2037521 |
| 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. |
| Uncontrolled Keywords: | agent-based simulation,gpu acceleration,mapk,systems biology |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications |
| Date Deposited: | 04 Apr 2014 14:14 |
| Last Modified: | 23 Sep 2021 14:32 |
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