activity
20182022
most citedAn In-Memory Analog Computing Co-Processor for Energy-Efficient CNN Inference on Mobile Devices

1 citations · 1 across the 13 of their papers we have counts for

collaborators

14 papers

cs.LG2022

Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware

Peyton Chandarana, Mohammadreza Mohammadi, James Seekings +1

As the technology industry is moving towards implementing tasks such as natural language processing, path planning, image classification, and more on smaller edge computing devices…

cs.LG2022

Reliability-Aware Deployment of DNNs on In-Memory Analog Computing Architectures

Md Hasibul Amin, Mohammed Elbtity, Ramtin Zand

Conventional in-memory computing (IMC) architectures consist of analog memristive crossbars to accelerate matrix-vector multiplication (MVM), and digital functional units to realiz…

cs.AR2022

A Python Framework for SPICE Circuit Simulation of In-Memory Analog Computing Circuits

Md Hasibul Amin, Mohammed Elbtity, Ramtin Zand

With the increased attention to memristive-based in-memory analog computing (IMAC) architectures as an alternative for energy-hungry computer systems for data-intensive application…

cs.NE2021

An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks

Peyton Chandarana, Junlin Ou, Ramtin Zand

Current state-of-the-art methods of image classification using convolutional neural networks are often constrained by both latency and power consumption. This places a limit on the…

cs.AR20211 cited

An In-Memory Analog Computing Co-Processor for Energy-Efficient CNN Inference on Mobile Devices

Mohammed Elbtity, Abhishek Singh, Brendan Reidy +2

In this paper, we develop an in-memory analog computing (IMAC) architecture realizing both synaptic behavior and activation functions within non-volatile memory arrays. Spin-orbit…

cs.ET2020

A Single-Cycle MLP Classifier Using Analog MRAM-based Neurons and Synapses

Ramtin Zand

In this paper, spin-orbit torque (SOT) magnetoresistive random-access memory (MRAM) devices are leveraged to realize sigmoidal neurons and binarized synapses for a single-cycle ana…