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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. ; 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.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2011
Autor(en): Falk, M. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H.
Art des Eintrags: Bibliographie
Titel: Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors
Sprache: Englisch
Publikationsjahr: 2011
Ort: New York, New York, USA
Verlag: ACM Press
Buchtitel: 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
Kurzbeschreibung (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.

Freie Schlagworte: agent-based simulation,gpu acceleration,mapk,systems biology
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
Hinterlegungsdatum: 04 Apr 2014 14:14
Letzte Änderung: 23 Sep 2021 14:32
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