Reducing the Impact of Phase-Change Memory Conductance Drift on the Inference of large-scale Hardware Neural Networks
- Stefano Ambrogio
- M. Gallot
- et al.
- 2019
- IEDM 2019
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27 results for An Chen
A Highly Efficient and Scalable Model for Crossbar Arrays with Nonlinear Selectors
- An Chen
- 2018
- IEDM 2018
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
An analog-AI chip for energy-efficient speech recognition and transcription
- S. Ambrogio
- Pritish Narayanan
- et al.
- 2023
- Nature
Optimization of Projected Phase Change Memory for Analog In-Memory Computing Inference
- Ning Li
- Charles Mackin
- et al.
- 2023
- Advanced Materials
Optimised weight programming for analogue memory-based deep neural networks
- Charles Mackin
- Malte J. Rasch
- et al.
- 2022
- Nature Communications
Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers
- Atsuya Okazaki
- Pritish Narayanan
- et al.
- 2022
- ISCAS 2022
Circuit techniques for efficient acceleration of deep neural network inference with Analog-AI (Invited)
- Kohji Hosokawa
- Pritish Narayanan
- et al.
- 2021
- ISCAS 2021
Inference of Deep Neural Networks with Analog Memory Devices
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2020
- VLSI-TSA 2020
Accelerating Deep Neural Networks with Analog Memory Devices
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2020
- AICAS 2020