Adaptive deployment of model reductions for tau-leaping simulation
Abstract
Multiple time scales in cellular chemical reaction systems often render the tau-leaping algorithm inefficient. Various model reductions have been proposed to accelerate tau-leaping simulations. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming and prone to error. In previous work, we proposed a methodology for automatic identification and validation of model reduction opportunities for tau-leaping simulation. Here, we show how the model reductions can be automatically and adaptively deployed during the time course of a simulation. For multiscale systems, this can result in substantial speedups.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 27, 2015
- Source ID
- 10.1063/1.4921638
Entities
People
- Jin Fu
- Linda Petzold
- Sheng Wu
Organizations
- Army Research Office
- National Institutes of Health
- National Science Foundation
- United States Department of Energy
- University of California, Santa Barbara