Aitken, Stewart ORCID: 0000-0002-6785-2019 (2022) An exploration of local rules to map spawning processes to regular hardware architectures. MSc by research thesis, University of York.
Abstract
This thesis presents an exploration of population growth via simulation in software to ascertain if a massively parallel hardware system can manage applications running within. Task execution happens dynamically and is controlled by the growth mechanism implementing efficient mapping in simulation. Algorithms that provide population simulation models are often inspired by those evidenced in biology and in particular those of cellular automata and L-systems. These algorithms are of particular interest due to their complexity and self-replication and recent research has shown that it is the refinement of the biological methodology that has resulted in their complexity. Further to this, adaptation of the design has moved the algorithm on towards being able to organize and build itself from a single cell. A growth model is utilized in software systems to provide production of meaningful data. The development of bio-inspired software is constrained by using contemporary processor architectures.
Metadata
Supervisors: | Stepney, Susan and Tempesti, Gianluca |
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Keywords: | growth; simulation; mapping |
Awarding institution: | University of York |
Academic Units: | The University of York > Computer Science (York) |
Depositing User: | Mr Stewart Aitken |
Date Deposited: | 04 Aug 2022 10:43 |
Last Modified: | 04 Aug 2022 10:43 |
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