18 citations · 42 across the 6 of their papers we have counts for
7 papers · 1 filter
Mitigating Imperfections in Mixed-Signal Neuromorphic Circuits
Z. Fahimi, M. R. Mahmoodi, M. Klachko +3
The progress in neuromorphic computing is fueled by the development of novel nonvolatile memories capable of storing analog information and implementing neural computation efficien…
Memristor Hardware-Friendly Reinforcement Learning
Nan Wu, Adrien Vincent, Dmitri Strukov +1
Recently, significant progress has been made in solving sophisticated problems among various domains by using reinforcement learning (RL), which allows machines or agents to learn…
3D-aCortex: An Ultra-Compact Energy-Efficient Neurocomputing Platform Based on Commercial 3D-NAND Flash Memories
Mohammad Bavandpour, Shubham Sahay, Mohammad Reza Mahmoodi +1
The first contribution of this paper is the development of extremely dense, energy-efficient mixed-signal vector-by-matrix-multiplication (VMM) circuits based on the existing 3D-NA…
4K-Memristor Analog-Grade Passive Crossbar Circuit
Hyungjin Kim, Hussein Nili, Mahmood Mahmoodi +1
The superior density of passive analog-grade memristive crossbars may enable storing large synaptic weight matrices directly on specialized neuromorphic chips, thus avoiding costly…
Improving Noise Tolerance of Mixed-Signal Neural Networks
Michael Klachko, Mohammad Reza Mahmoodi, Dmitri B. Strukov
Mixed-signal hardware accelerators for deep learning achieve orders of magnitude better power efficiency than their digital counterparts. In the ultra-low power consumption regime,…
A Behavioral Compact Model of 3D NAND Flash Memory
Shubham Sahay, Dmitri Strukov
We present a behavioral compact model of 3D NAND flash memory for integrated circuits and system-level applications. This model is easy to implement, computationally efficient, fas…