Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
- Malte J. Rasch
- Charles Mackin
- et al.
- 2023
- Nature Communications
Publications
109 results for Manuel Le Gallo-Bourdeau
Deep neural network inference with a 64-core in-memory compute chip based on phase-change memory
- 2023
- NVMTS 2023
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
- et al.
- 2023
- Nature Electronics
AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing
- Hadjer Benmeziane
- Corey Lammie
- et al.
- 2023
- EDGE 2023
In-memory computing for accelerating deep neural networks and neuro-vector-symbolic architectures
- 2023
- AICAS 2023
Deep learning inference using computational phase-change memory
- 2023
- HPCA 2023
Exploiting the State Dependency of Conductance Variations in Memristive Devices for Accurate In-Memory Computing
- 2023
- IEEE T-ED
Gradient descent-based programming of analog in-memory computing cores
- 2022
- IEDM 2022
Optimised weight programming for analogue memory-based deep neural networks
- Charles Mackin
- Malte Rasch
- et al.
- 2022
- MRS Fall Meeting 2022
Deep learning inference and training using computational phase-change memory
- 2022
- MRS Fall Meeting 2022