Superconducting nanowire electronics for alternative computing
Name
1191230092-MIT.pdf
Size
13.05 MB
Format
Adobe PDF
Checksum (MD5)
370176a5e58572b36f7d9fe3d99b4d2f
Author(s)
Toomey, Emily.
Advisor(s)
Karl K. Berggren.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
With traditional computing systems struggling to meet the demands of modern technology, new approaches to both hardware and architecture are becoming increasingly critical. In this work, I develop the foundation of a power-efficient alternative computing system using superconducting nanowires. Although traditionally operated as single photon detectors, superconducting nanowires host a suite of attractive characteristics that have recently inspired their use in digital circuit applications for amplification, addressing, and memory. Here, I take advantage of the electrothermal feedback that occurs in resistively shunted nanowires to develop two new technologies: (1) A multilevel memory cell made by incorporating a shunted nanowire into a superconducting loop, allowing flux to be controllably added and stored; and (2) An artificial neuron for use in spiking neural networks, consisting of two nanowire-based relaxation oscillators acting analogously to the two ion channels in a biological neuron. By harnessing the intrinsic dynamics of superconducting nanowires, these devices offer competitive energy performance and a step towards bringing memory and processing closer together on the same platform.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 141-153).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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