RSFQ digital circuit design automation and optimisation

Thesis (PhD)--Stellenbosch University, 2015. === ENGLISH ABSTRACT: In order to facilitate the creation of complex and robust RSFQ digital logic circuits an extensive library of electronic design automation (EDA) tools is a necessity. It is the aim of this work to introduce various methods to impro...

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Main Author: Muller, Louis C.
Other Authors: Fourie, Coenrad J.
Format: Others
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2015
Subjects:
Online Access:http://hdl.handle.net/10019.1/96808
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-sun-oai-scholar.sun.ac.za-10019.1-968082016-01-29T04:02:12Z RSFQ digital circuit design automation and optimisation Muller, Louis C. Fourie, Coenrad J. Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. RSFQ digital circuit design -- Automation Rapid Single Flux Quantum (RSFQ) RSFQ digital circuit design -- Optimisation UCTD Thesis (PhD)--Stellenbosch University, 2015. ENGLISH ABSTRACT: In order to facilitate the creation of complex and robust RSFQ digital logic circuits an extensive library of electronic design automation (EDA) tools is a necessity. It is the aim of this work to introduce various methods to improve the current state of EDA in RSFQ circuit design. Firstly, Monte Carlo methods such as Latin Hypercube sampling and Sobol sequences are applied for their variance reduction abilities in approximating circuit yield. In addition, artificial neural networks are also investigated for their applicability in modeling the parameter-yield space. Secondly, a novel technique for circuit functional testing using automated state machine extraction is presented, which greatly simplifies the logical verification of a circuit. This method is also used, along with critical timing extraction, to automatically generate Hardware Description Language(HDL) models which can be used for high level circuit design. Lastly, the Greedy Local search, Simulated Annealing and Genetic Algorithm meta-heuristics were statistically compared in a novel manner using a yield model provided by artificial neural networks. This is done to ascertain their performance in optimising RSFQ circuits in relation to yield. The variance reduction techniques of Latin Hypercube Sampling and Sobol sequences were shown to be beneficial for the use with RSFQ circuits. For optimisation purposes the use of Simulated Annealing and Genetic Algorithms were shown to improve circuit optimisation for possible multi-modal search spaces. An HDL model is also successfully generated from a complex RSFQ circuit for use in high level circuit design which includes critical timing and propagation latency. All the techniques presented in this study form part of a software library that can be further refined and extended in future work. 2015-05-20T09:27:37Z 2015-05-20T09:27:37Z 2015-03 Thesis http://hdl.handle.net/10019.1/96808 en_ZA Stellenbosch University 151 pages : illustrations Stellenbosch : Stellenbosch University
collection NDLTD
language en_ZA
format Others
sources NDLTD
topic RSFQ digital circuit design -- Automation
Rapid Single Flux Quantum (RSFQ)
RSFQ digital circuit design -- Optimisation
UCTD
spellingShingle RSFQ digital circuit design -- Automation
Rapid Single Flux Quantum (RSFQ)
RSFQ digital circuit design -- Optimisation
UCTD
Muller, Louis C.
RSFQ digital circuit design automation and optimisation
description Thesis (PhD)--Stellenbosch University, 2015. === ENGLISH ABSTRACT: In order to facilitate the creation of complex and robust RSFQ digital logic circuits an extensive library of electronic design automation (EDA) tools is a necessity. It is the aim of this work to introduce various methods to improve the current state of EDA in RSFQ circuit design. Firstly, Monte Carlo methods such as Latin Hypercube sampling and Sobol sequences are applied for their variance reduction abilities in approximating circuit yield. In addition, artificial neural networks are also investigated for their applicability in modeling the parameter-yield space. Secondly, a novel technique for circuit functional testing using automated state machine extraction is presented, which greatly simplifies the logical verification of a circuit. This method is also used, along with critical timing extraction, to automatically generate Hardware Description Language(HDL) models which can be used for high level circuit design. Lastly, the Greedy Local search, Simulated Annealing and Genetic Algorithm meta-heuristics were statistically compared in a novel manner using a yield model provided by artificial neural networks. This is done to ascertain their performance in optimising RSFQ circuits in relation to yield. The variance reduction techniques of Latin Hypercube Sampling and Sobol sequences were shown to be beneficial for the use with RSFQ circuits. For optimisation purposes the use of Simulated Annealing and Genetic Algorithms were shown to improve circuit optimisation for possible multi-modal search spaces. An HDL model is also successfully generated from a complex RSFQ circuit for use in high level circuit design which includes critical timing and propagation latency. All the techniques presented in this study form part of a software library that can be further refined and extended in future work.
author2 Fourie, Coenrad J.
author_facet Fourie, Coenrad J.
Muller, Louis C.
author Muller, Louis C.
author_sort Muller, Louis C.
title RSFQ digital circuit design automation and optimisation
title_short RSFQ digital circuit design automation and optimisation
title_full RSFQ digital circuit design automation and optimisation
title_fullStr RSFQ digital circuit design automation and optimisation
title_full_unstemmed RSFQ digital circuit design automation and optimisation
title_sort rsfq digital circuit design automation and optimisation
publisher Stellenbosch : Stellenbosch University
publishDate 2015
url http://hdl.handle.net/10019.1/96808
work_keys_str_mv AT mullerlouisc rsfqdigitalcircuitdesignautomationandoptimisation
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