Accelerating Finite State Projection through General Purpose Graphics Processing

The finite state projection algorithm provides modelers a new way of directly solving the chemical master equation. The algorithm utilizes the matrix exponential function, and so the algorithm’s performance suffers when it is applied to large problems. Other work has been done to reduce the size of the exponentiation through mathematical simplifications, but efficiently exponentiating a large matrix has not been explored. This work explores implementing the finite state projection algorithm on several different high-performance computing platforms as a means of efficiently calculating the matrix exponential function for large systems. This work finds that general purpose graphics processing can accelerate the finite state projection algorithm by several orders of magnitude. Specific biological models and modeling techniques are discussed as a demonstration of the algorithm implemented on a general purpose graphics processor. The results of this work show that general purpose graphics processing will be a key factor in modeling more complex biological systems.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Engineering

Year dc:date.available

2011

Author dc:creator

• Trimeloni, Thomas

Contributors dc:contributor

• James McCollum

• Finite State Projection
• Systems Biology
• High-Performance Computing
• Graphics Processing
• Modeling
• Gillespie Algorithm
• Chemical Master Equation
• Differential Equations
• Stochastic Simulation
• Engineering

Statement dc:rights

• © The Author

Identifier

https://scholarscompass.vcu.edu/etd/175

OAI identifier oai:identifier

oai:scholarscompass.vcu.edu:etd-1174