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20172023
most citedMonatomic phase change memory

312 citations · 473 across the 17 of their papers we have counts for

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12 papers · 1 filter

cs.ET2023★ 66 cited

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference

Manuel Le Gallo, Corey Lammie, Julian Buechel +8

Analog In-Memory Computing (AIMC) is a promising approach to reduce the latency and energy consumption of Deep Neural Network (DNN) inference and training. However, the noisy and n…

cs.ET2022

A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference

Manuel Le Gallo, Riduan Khaddam-Aljameh, Milos Stanisavljevic +26

The need to repeatedly shuttle around synaptic weight values from memory to processing units has been a key source of energy inefficiency associated with hardware implementation of…

cs.ET2021★ 21 cited

Energy Efficient In-memory Hyperdimensional Encoding for Spatio-temporal Signal Processing

Geethan Karunaratne, Manuel Le Gallo, Michael Hersche +4

The emerging brain-inspired computing paradigm known as hyperdimensional computing (HDC) has been proven to provide a lightweight learning framework for various cognitive tasks com…

cs.ET2020★ 1 cited

Memristors -- from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing

Adnan Mehonic, Abu Sebastian, Bipin Rajendran +3

Machine learning, particularly in the form of deep learning, has driven most of the recent fundamental developments in artificial intelligence. Deep learning is based on computatio…

cs.ET2020

Accurate Emulation of Memristive Crossbar Arrays for In-Memory Computing

Anastasios Petropoulos, Irem Boybat, Manuel Le Gallo +3

In-memory computing is an emerging non-von Neumann computing paradigm where certain computational tasks are performed in memory by exploiting the physical attributes of the memory…

cs.ET2020

Mixed-precision deep learning based on computational memory

S. R. Nandakumar, Manuel Le Gallo, Christophe Piveteau +11

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition…