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
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51 results for Pritish Narayanan
An analog-AI chip for energy-efficient speech recognition and transcription
- S. Ambrogio
- Pritish Narayanan
- et al.
- 2023
- Nature
A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh
- Shubham Jain
- Hsinyu Tsai
- et al.
- 2023
- IEEE Transactions on VLSI Systems
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
Fully On-Chip MAC at 14 nm Enabled by Accurate Row-Wise Programming of PCM-Based Weights and Parallel Vector-Transport in Duration-Format
- Pritish Narayanan
- Stefano Ambrogio
- et al.
- 2021
- IEEE T-ED
Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training
- Sanjay Kariyappa
- Hsinyu Tsai
- et al.
- 2021
- IEEE T-ED
Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices
- Katherine Spoon
- Hsinyu Tsai
- et al.
- 2021
- Frontiers in Computational Neuroscience
Fully on-chip MAC at 14nm enabled by accurate row-wise programming of PCM-based weights and parallel vector-transport in duration-format
- P. Narayanan
- S. Ambrogio
- et al.
- 2021
- VLSI 2021
Circuit techniques for efficient acceleration of deep neural network inference with Analog-AI (Invited)
- Kohji Hosokawa
- Pritish Narayanan
- et al.
- 2021
- ISCAS 2021