MRS Meetings and Events

 

EQ11.04.02 2022 MRS Spring Meeting

High-Performance Neuromorphic Optimization with Analog Nonvolatile Memory Circuits

When and Where

May 10, 2022
2:00pm - 2:30pm

Hawai'i Convention Center, Level 3, 318A

Presenter

Co-Author(s)

Dmitri Strukov1

University of California, Santa Barbara1

Abstract

Dmitri Strukov1

University of California, Santa Barbara1
Stochastic neural networks have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics. The critical operation in such networks is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, stochastic neurons, the efficient hardware implementation combining both functionalities is still missing. In my talk, I will discuss our recent work on addressing this need. I will start with the discussion of compact, fast, energy-efficient, and scalable stochastic dot-product circuits based on passively integrated metal-oxide memristors. The high performance of such circuits is due to mixed-signal implementation enabling energy-saving in-memory computing. The stochastic functionality is achieved by operating the circuit in a low signal-to-noise ratio regime by utilizing the circuit’s noise, intrinsic and/or extrinsic to the memory cell array. I will then discuss several application demonstrations based on passively integrated TiO2-x memristors, including Hopfield networks for solving optimization problems and a Boltzmann machine. In the proposed circuits the neuron outputs can be selectively scaled which allows adjusting coupling between the neurons and/or controlling the signal-to-noise ratio at runtime, without the need to rewrite the memory weights. This feature enables, for example, efficient implementation of different annealing approaches that improve the quality of the solution for the solved optimization problems. I will conclude my talk with a comparison of the proposed approach to other solutions based on the conventional and emerging technologies, and a discussion of the future important work.

Symposium Organizers

Yoeri van de Burgt, Technische Universiteit Eindhoven
Yiyang Li, University of Michigan
Francesca Santoro, Forschungszentrum Jülich/RWTH Aachen University
Ilia Valov, Research Center Juelich

Symposium Support

Bronze
Nextron Corporation

Publishing Alliance

MRS publishes with Springer Nature