Klingbeil, G. and Erban, R. and Giles, M. B. and Maini, P. K. (2011) STOCHSIMGPU: parallel stochastic simulation for the sytems biology toolbox 2 for matlab. Bioinformatics, 27 (8). pp. 11701171.

PDF
132kB  

PDF
172kB  

PDF
284kB  

PDF
183kB 
Abstract
Motivation: The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB.
Results: The GPUbased parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2.
Availability: The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information.
Item Type:  Article 

Subjects:  A  C > Biology and other natural sciences 
Research Groups:  Centre for Mathematical Biology 
ID Code:  1060 
Deposited By:  Philip Maini 
Deposited On:  21 Apr 2011 07:32 
Last Modified:  29 May 2015 18:45 
Repository Staff Only: item control page