Event
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.
