Models of computation: A numeric analysis and performance evaluation

Verschueren, Ricardo (2014) Models of computation: A numeric analysis and performance evaluation. Masters thesis, University of Gloucestershire.

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Abstract

This research seeks to better understand what drives performance in computation. To develop this understanding the researcher investigates the literature on computational performance within the classical and quantum paradigm for both binary and multi-value logic. Based on the findings of the literature the researcher evaluates through an experiment of addition what drives performance and how performance can be improved. For the evaluation of this research, a realist research paradigm employs two research methods. The first is an automaton model of computation to model each of the computing paradigms and computational logic. The second is computational complexity theory for measuring the performance of addition. Through this evaluation the researcher seeks to gain a better understanding of what drives computational performance and how addition can be performed more efficiently. The results of the research lead the researcher to conclude that modernisation of machinery caused the birth start of automated computing and the binary number system in computers. As this research indicated that computation through increasing the radix can improve performance of computation for addition. Based on reported findings in the science of quantum mechanics research, it would be possible to implement a model of computation with increased radix. Through embracing state discrimination/ distinguishability this research calls to review the current quantum computing paradigm based on state duality.

Item Type: Thesis (Masters)
Thesis Advisors:
Thesis AdvisorEmailURL
Jayal, Ambikeshajayal@glos.ac.ukUNSPECIFIED
Hapeshi, Kevinkhapeshi@glos.ac.ukUNSPECIFIED
Uncontrolled Keywords: Computers,Performance improvement, Computational model, Multi-valued logic, Quantum theory, Quantum computing duality (mathematics)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Business, Computing and Applied Sciences > School of Computing and Technology
Depositing User: Susan Turner
Date Deposited: 23 Jul 2015 11:07
Last Modified: 22 Sep 2016 13:09
URI: http://eprints.glos.ac.uk/id/eprint/2493

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