Accelerating large dimensional stochastic simulation models

Bioeconomic simulation models are a critical tool used to estimate both the impacts that might be caused by pests or diseases and the relative value of the various interventions that we deploy to manage them.

Typically, these models describe the impacts of a single species on a single asset at relatively small spatial and temporal scales. Management agencies, however, are required to take an ‘all hazards’ approach when determining how they might best protect assets from the negative impacts of pests and disease at state and national scales.

The ‘value model,’ developed at the University of Melbourne, is the only model globally that is capable of simultaneously modelling the arrival, spread and impact of multiple biological hazards on multiple assets over time. However, in order to be effectively deployed within management agencies, or expanded for additional research use, the core architecture of the model needs to be faster.

This project will explore a range of options for improving the performance of the model spanning: how the dispersal of organisms is modelled, how the model is encoded, how compute resources are utilised and how the result data is stored. Improvements in any (or all) of these areas will enable uptake of the model into real-world decision-making contexts ultimately delivering improved biosecurity outcomes for society.