Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers
- Atsuya Okazaki
- Pritish Narayanan
- et al.
- 2022
- ISCAS 2022
Conference paper
Publications
13 results for Katherine Spoon
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
PaperNoise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training
- Sanjay Kariyappa
- Hsinyu Tsai
- et al.
- 2021
- IEEE T-ED
PaperToward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices
- Katherine Spoon
- Hsinyu Tsai
- et al.
- 2021
- Frontiers in Computational Neuroscience
PaperFully 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
Conference paperCircuit techniques for efficient acceleration of deep neural network inference with Analog-AI (Invited)
- Kohji Hosokawa
- Pritish Narayanan
- et al.
- 2021
- ISCAS 2021
Conference paperMushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation
- Robert L. Bruce
- Syed Ghazi Sarwat
- et al.
- 2021
- IRPS 2021
Conference paperInference of Deep Neural Networks with Analog Memory Devices
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2020
- VLSI-TSA 2020
Conference paperAccelerating Deep Neural Networks with Analog Memory Devices
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2020
- AICAS 2020
Conference paperAccelerating Deep Neural Networks with Analog Memory Devices
- Katherine Spoon
- Stefano Ambrogio
- et al.
- 2020
- IMW 2020
Conference paper