2 citations · 5 across the 5 of their papers we have counts for
5 papers
PRUNIX: Non-Ideality Aware Convolutional Neural Network Pruning for Memristive Accelerators
Ali Alshaarawy, Amirali Amirsoleimani, Roman Genov
In this work, PRUNIX, a framework for training and pruning convolutional neural networks is proposed for deployment on memristor crossbar based accelerators. PRUNIX takes into acco…
SDEX: Monte Carlo Simulation of Stochastic Differential Equations on Memristor Crossbars
Louis Primeau, Amirali Amirsoleimani, Roman Genov
Here we present stochastic differential equations (SDEs) on a memristor crossbar, where the source of gaussian noise is derived from the random conductance due to ion drift in the…
HYPERLOCK: In-Memory Hyperdimensional Encryption in Memristor Crossbar Array
Jack Cai, Amirali Amirsoleimani, Roman Genov
We present a novel cryptography architecture based on memristor crossbar array, binary hypervectors, and neural network. Utilizing the stochastic and unclonable nature of memristor…
Design Space Exploration of Dense and Sparse Mapping Schemes for RRAM Architectures
Corey Lammie, Jason K. Eshraghian, Chenqi Li +4
The impact of device and circuit-level effects in mixed-signal Resistive Random Access Memory (RRAM) accelerators typically manifest as performance degradation of Deep Learning (DL…
AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators
Tony Liu, Amirali Amirsoleimani, Fabien Alibart +3
An adaptive inference method for crossbar (AIDX) is presented based on an optimization scheme for adjusting the duration and amplitude of input voltage pulses. AIDX minimizes the l…