Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:A1L-B

Session:

Number:29

Coarse grain parallelization and acceleration of biochemical ODE simulation using GPGPU

Kazushige Nakamura,  Kei Sumiyoshi,  Noriko Hiroi,  Akira Funahashi,  

pp.29-32

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.29

PDF download (344.8KB)

Summary:
We have accelerated the simulation of biochemical ODE model described in SBML(Systems Biology Markup Language), by using the parallel processing approach on GPU. Compared with the implementation on CPU, our simulator have accelerated about 12 times faster in a single-precision number, and 10 times faster in a double-precision. In this research, we have implemented the simulator which have the function to read models dynamically from SBML files, and simulates the model on GPU. Several existing works have done which numerically solves ODE on GPU. However, those simulators could not read models dynamically without generating a code for every model. Our work achieved better portability than previous researches by reading models dynamically from SBML files, without a re-compiling of the codes. We implemented the solver by the classical Runge-kutta method, which has known to be a basic factor of other solvers, therefore we can develop advanced solvers in the future based on our current simulator.

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