FLAME: simulating large populations of agents on parallel hardware architectures

Abstract

High performance computing is essential for simulating complex problems using agent-based modelling (ABM). Researchers are hindered by complexities of porting models on parallel platforms and time taken to run large simulations on a single machine. This paper presents FLAME framework, the only supercomputing framework which automatically produces parallelisable code to execute on different parallel hardware architectures. FLAME's inherent parallelism allows large number of agents to be simulated in less time than comparable simulation frameworks. The framework also handles the parallelisation of model code allowing modellers to run simulations on number of supported architectures.The framework has been well tested in various disciplines like biology and economics projects yielding successful research results like project EURACE, where the European economy was modelled using agents. More recently FLAME has been ported to consumer NVIDIA Graphics Processing Units (GPUs) allowing parallel performance equal to that of grid architectures with the ability to perform real time visualisation.