Phase-change memory models for deep learning training and inference
- S. R. Nandakumar
- Irem Boybat
- et al.
- 2019
- ICECS 2019
Publications
Date
Featured collections
Popular topics
100 results for Manuel Le Gallo-Bourdeau
Phase-change memory enables energy-efficient brain-inspired computing
- 2019
- DRC 2019
Computational memory-based inference and training of deep neural networks
- Abu Sebastian
- Irem Boybat
- et al.
- 2019
- VLSI Circuits 2019
Multi-ReRAM synapses for artificial neural network training
- Irem Boybat
- Cecilia Giovinazzo
- et al.
- 2019
- ISCAS 2019
Applications of Computation-In-Memory Architectures based on Memristive Devices
- Said Hamdioui
- Hoang Anh Du Nguyen
- et al.
- 2019
- DATE 2019
All-Photonic in-Memory Computing Based on Phase-Change Materials
- Carlos Ríos
- Nathan Youngblood
- et al.
- 2019
- CLEO 2019
Training neural networks using memristive devices with nonlinear accumulative behavior
- Christophe Piveteau
- Manuel Le Gallo
- et al.
- 2019
- IMW 2019
Impact of conductance drift on multi-PCM synaptic architectures
- Irem Boybat
- S. R. Nandakumar
- et al.
- 2018
- NVMTS 2018
Mixed-precision architecture based on computational memory for training deep neural networks
- S. R. Nandakumar
- Manuel Le Gallo
- et al.
- 2018
- ISCAS 2018
An efficient synaptic architecture for artificial neural networks
- 2017
- NVMTS 2017