BIRS Workshop Lecture Videos
Lazy Updating increases the speed of stochastic simulations Ehlert, Kurt
Many biological reaction networks contain molecules involved in many reactions. For example, ATP is often consumed or produced. When reaction networks contain molecules like ATP, they are difficult to efficiently simulate, because every time such a molecule is consumed or produced, many propensity updates need to occur. In order to increase the speed of simulations, we developed the “Lazy Updating” method, which postpones propensity updates. Lazy Updating can be used in conjunction with many stochastic simulation algorithms, including Gillespie’s direct method and the Next Reaction Method.\\r\\n\\r\\nWe tested Lazy Updating on two example systems and found that it substantially increased the speed of simulations. We derived a formula predicting the expected speed increase and showed that the empirical speed increase matches our expectation closely. According to our results, Lazy Updating trades off a small amount of accuracy for a large speed increase. Since Lazy Updating enhances our ability to quickly simulate large reaction networks, it is a useful add-on to existing stochastic simulation algorithms.
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