activity
20192021
most citedIn-Memory and Error-Immune Differential RRAM Implementation of Binarized Deep Neural Networks

83 citations · 89 across the 6 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

physics.app-ph2020

Improvement of HRS Variability in OxRRAM by Tailored Metallic Liner

N. Guillaume, M. Azzaz, S. Blonkowski +9

In this work, we propose a novel integration in order to significantly reduce the High Resistance State vari-ability and to improve thermal stability in Oxide-based Resistive Rando…

cs.ET2020

Embracing the Unreliability of Memory Devices for Neuromorphic Computing

Marc Bocquet, Tifenn Hirtzlin, Jacques-Olivier Klein +4

The emergence of resistive non-volatile memories opens the way to highly energy-efficient computation near- or in-memory. However, this type of computation is not compatible with c…

cs.ET2020

Implementation of Ternary Weights with Resistive RAM Using a Single Sense Operation per Synapse

Axel Laborieux, Marc Bocquet, Tifenn Hirtzlin +5

The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a significant lead for reducing the energy…

eess.SP2020

In-Memory Resistive RAM Implementation of Binarized Neural Networks for Medical Applications

Bogdan Penkovsky, Marc Bocquet, Tifenn Hirtzlin +5

The advent of deep learning has considerably accelerated machine learning development. The deployment of deep neural networks at the edge is however limited by their high memory an…

cs.ET2020

Low Power In-Memory Implementation of Ternary Neural Networks with Resistive RAM-Based Synapse

Axel Laborieux, Marc Bocquet, Tifenn Hirtzlin +6

The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a major lead for reducing the energy consum…