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Title: Spatial reaction systems on parallel supercomputers
Author: Smith, Mark
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1994
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A wide variety of physical, chemical and biological systems can be represented as a collection of discrete spatial locations within which some interaction proceeds, and between which reactants diffuse or migrate. Many such real-world spatial reaction systems are known to be both non-linear and stochastic in nature, and thus studies of these systems have generally relied upon analytic approximation and computer simulation. However, this later approach can become impractical for large, complex systems which require massive computational resources. In this work we analyse a general spatial reaction system in both the deterministic and stochastic scenarios. A study of the deterministic parameter space reveals a new categorisation for system development in terms of its criticality. This result is then coupled with a complete analysis of the linearised stochastic system, in order to provide an understanding of the spatial-temporal covariance structures within reactant distributions. In addition to an analysis, and empirical confirmation, of the various criticality behaviours in both deterministic and stochastic cases, we use our theoretical results to enable efficient implementation of spatial reaction system simulations on parallel supercomputers. Such novel computing resources are necessary to enable the study of realistic-scale, long-term stochastic activity, however they are notoriously difficult to exploit. We have therefore developed advanced programming and implementation techniques, concentrating mainly on dynamic load-balancing methodologies, to enable such studies. These techniques make direct use of our analytic results in order to achieve the most efficient exploitation of supercomputing resources, given the particular attributes of the system under study. These new techniques have allowed us to investigate complex individual-based systems on a previously untried scale. In addition, they are of general applicability to a wide range of real-world simulations.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available