| 1. |
- Falk, Martin, et al.
(author)
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Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology
- 2011
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In: Proceedings of the 9th International Conference on Computational Methods in Systems Biology, CMSB'112011. - New York, NY, USA : ACM Press. - 9781450308175 ; , s. 73-82
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Conference paper (peer-reviewed)abstract
- The complexity of biological systems is enormous, even when considering a single cell where a multitude of highly parallel and intertwined processes take place on the molecular 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 discretetime continuous-space random walk to model its diffusion through the cell. Since the interactions and reactions between 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 simulation to model signal transduction in the MAPK (Mitogen-Activated Protein Kinase) cascade both with and without cytoskeletal filaments. Finally, we compare the speed-up of our GPU simulation with a parallelized CPU version resulting in a twelvefold speedup.
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| 2. |
- Huang, Lirong, et al.
(author)
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Almost sure stability and stabilization of discrete-time stochastic systems
- 2015
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In: Systems & control letters (Print). - : Elsevier BV. - 0167-6911 .- 1872-7956. ; 82, s. 26-32
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Journal article (peer-reviewed)abstract
- As is well known, noise may play a stabilizing or destabilizing role in continuous-time systems. But, for analysis and design of discrete-time systems, noise is treated as disturbance in the literature. This paper studies almost sure stability of general n-dimensional nonlinear time-varying discrete-time stochastic systems and presents a criterion based on a numerical result derived from Higham (2001), which exploits the stabilizing role of noise in discrete-time systems. As an application of the established results, this paper proposes a novel controller design method for almost sure-stabilization of linear discrete-time stochastic systems. The effectiveness of the proposed design method is verified with an example (an aircraft model subject to state-dependent noise), to which the existing results do not apply.
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