Ph.D. Research Proposal Exam: Heidi Komkov

Tuesday, August 4, 2020
3:00 p.m.
https://zoom.us/j/6179028404
Emily Irwin
301 405 0680
eirwin@umd.edu

ANNOUNCEMENT: Ph.D. Research Proposal Exam

Name: Heidi Komkov

Committee:

Professor Daniel Lathrop (Chair)

Professor Timothy Horiuchi

Professor Pamela Abshire 

Date/time: August 4th, 3PM 

 Location: https://zoom.us/j/6179028404

 

Title: Reservoir Computing ASICs Using Autonomous Boolean Logic Networks: Hardware for High-Speed Machine Learning

 

Abstract: As Moore's law is coming to an end, new types of computing architectures must be explored to continue the pace of advancement in computing power. At the same time, applications of machine learning are exploding. Reservoir computing is a brain-inspired machine learning method which has shown promise for very rapid time series prediction. The reservoir functions as a recurrent neural network, and substituting a physical system for a computer-based simulation has the potential to allow computation at high speed and very low power. We use an autonomous Boolean network as a reservoir, which uses digital logic gates manufactured using conventional CMOS processes, to perform analog computation. In this proposal I will discuss my designs of reservoir computing ASICs which are currently in production.

Audience: Faculty 

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