Chris Greenough

Exploitation of High Performance Computing in the FLAME Agent-Based Simulation Framework

This paper describes the design of an agent-based modelling framework for high performance computing. Rather than a collection of methods that require parallel programming expertise the framework presented allows modellers to concentrate on the model while the framework handles the efficient execution of simulations. The framework uses a state machine based representation of agents that allows a statically calculated optimal ordering of agent execution and parallel communication routines. Some experiments with the current implementation and the results of using a simple communication dominant model for benchmarking performance are reported. The model with half a million agents is used to show that a parallel efficiency of above 80% is achievable when distributed over 432 processors. Future improvements are discussed including data dependency analysis, vector operations over agents, and dynamic task scheduling.

Large-Scale Simulations with FLAME

This chapter presents the latest stage of the FLAME development—the high-performance environment FLAME-II and the parallel architecture designed for Graphics Processing Units, FLAMEGPU. The architecture and the performances of these two agent-based software environments are presented, together with illustrative large-scale simulations for systems from biology, economy, psychology and crowd behaviour applications.

Software for Partitioning Finite Element Meshes

Mesh partitioning methods for parallel processing aim to split up unstructured meshes to give computational load balance while minimising the interprocessor communication time. Due to the computational cost of an exhaustive search of all possible partitionings many heuristic methods have been developed for this task. We present details of a software program that implements a wide range of partitioning methods to allow easy comparison of method costs and results. It also contains some simple models of communication to estimate the true communication times that result from a given partitioning.