175 citations · 343 across the 24 of their papers we have counts for
17 papers · 1 filter
Multilayer spintronic neural networks with radio-frequency connections
Andrew Ross, Nathan Leroux, Arnaud de Riz +18
Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. Thes…
Experimental demonstration of Single-Level and Multi-Level-Cell RRAM-based In-Memory Computing with up to 16 parallel operations
E. Esmanhotto, T. Hirtzlin, N. Castellani +7
Crossbar arrays of resistive memories (RRAM) hold the promise of enabling In-Memory Computing (IMC), but essential challenges due to the impact of device imperfection and device en…
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…
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…
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…
Physics for Neuromorphic Computing
Danijela Markovic, Alice Mizrahi, Damien Querlioz +1
Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we m…