A Low-Power Domino Logic Architecture for Memristor-Based Neuromorphic Computing

06/13/2019
by   Cory Merkel, et al.
0

We propose a domino logic architecture for memristor-based neuromorphic computing. The design uses the delay of memristor RC circuits to represent synaptic computations and a simple binary neuron activation function. Synchronization schemes are proposed for communicating information between neural network layers, and a simple linear power model is developed to estimate the design's energy efficiency for a particular network size. Results indicate that the proposed architecture can achieve 0.61 fJ per classification per component (neurons and synapses) and outperforms other designs in terms of energy per

READ FULL TEXT
research
06/13/2018

Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons

Neuromorphic computing, inspired by the brain, promises extreme efficien...
research
10/04/2022

Logic and learning in network cascades

Critical cascades are found in many self-organizing systems. Here, we ex...
research
02/18/2013

A Low-Power Content-Addressable-Memory Based on Clustered-Sparse-Networks

A low-power Content-Addressable-Memory (CAM) is introduced employing a n...
research
04/03/2019

Low Power Artificial Neural Network Architecture

Recent artificial neural network architectures improve performance and p...
research
10/16/2018

Critical Neuromorphic Computing based on Explosive Synchronization

Synchronous oscillations in neuronal ensembles have been proposed to pro...
research
03/23/2020

A 75kb SRAM in 65nm CMOS for In-Memory Computing Based Neuromorphic Image Denoising

This paper presents an in-memory computing (IMC) architecture for image ...
research
12/10/2022

Neuromorphic Computing and Sensing in Space

The term “neuromorphic” refers to systems that are closely resembling th...

Please sign up or login with your details

Forgot password? Click here to reset