Parallel simulation methods for large-scale agent-based predator-prey systems : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Albany, New Zealand

dc.contributor.authorQuach, Dara (Minh) Quang
dc.date.accessioned2020-11-11T23:31:48Z
dc.date.available2020-11-11T23:31:48Z
dc.date.issued2019
dc.description.abstractThe Animat is an agent-based artificial-life model that is suitable for gaining insight into the interactions of autonomous individuals in complex predator-prey systems and the emergent phenomena they may exhibit. Certain dynamics of the model may only be present in large systems, and a large number of agents may be required to compare with macroscopic models. Large systems can be infeasible to simulate on single-core machines due to processing time required. The model can be parallelised to improve the performance; however, reproducing the original model behaviour and retaining the performance gain is not straightforward. Parallel update strategies and data structures for multi-core CPU and graphical processing units (GPUs) are developed to simulate a typical predator-prey Animat model with improved perfor- mance while reproducing the behaviour of the original model. An analysis is presented of the model to identify dependencies and conditions the parallel update strategy must satisfy to retain original model behaviour. The parallel update strategy for multi-core CPUs is constructed using a spatial domain decomposition approach and supporting data structure. The GPU implementation is developed with a new update strategy that consists of an iterative conflict resolution method and priority number system to simultaneously update many agents with thousands of GPU cores. This update method is supported by a compressed sparse data structure developed to allow for efficient memory transactions. The performance of the Animat simulation is improved with parallelism and without a change in model behaviour. The simulation usability is considered, and an internal agent definition system using a CUDA device Lambda feature is developed to improve the ease of configuring agents without significant changes to the program and loss of performance.en_US
dc.identifier.urihttp://hdl.handle.net/10179/15802
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectPredation (Biology)en_US
dc.subjectAnimal behavioren_US
dc.subjectSimulation methodsen_US
dc.subjectMultiagent systemsen_US
dc.subjectParallel processing (Electronic computers)en_US
dc.subject.anzsrc460207 Modelling and simulationen
dc.titleParallel simulation methods for large-scale agent-based predator-prey systems : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Albany, New Zealanden_US
dc.typeThesisen_US
massey.contributor.authorQuach, Dara (Minh) Quang
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
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