Analog-to-Digital Conversion with Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration
- Massimo Giordano
- Giorgio Cristiano
- et al.
- 2019
- IEEE JESTCS
Paper
Publications
53 results for Pritish Narayanan
Neuro-inspired computing: From resistive memory to optics
- Charles Mackin
- Pritish Narayanan
- et al.
- 2019
- CLEO/Europe-EQEC 2019
Conference paperInference of Long-Short Term Memory networks at software-equivalent accuracy using 2.5M analog Phase Change Memory devices
- Hsinyu Tsai
- Stefano Ambrogio
- et al.
- 2019
- VLSI Technology 2019
Conference paperAccelerating deep neural networks with analog memory devices
- Geoffrey W. Burr
- Stefano Ambrogio
- et al.
- 2019
- CSTIC 2019
Conference paperTraining fully connected networks with resistive memories: Impact of device failures
- Louis P. Romero
- Stefano Ambrogio
- et al.
- 2019
- Faraday Discussions
PaperPerspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance
- Giorgio Cristiano
- Massimo Giordano
- et al.
- 2018
- Journal of Applied Physics
PaperRecent progress in analog memory-based accelerators for deep learning
- Hsinyu Tsai
- Stefano Ambrogio
- et al.
- 2018
- Journal of Physics D: Applied Physics
ReviewEquivalent-accuracy accelerated neural-network training using analogue memory
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2018
- Nature
PaperBidirectional non-filamentary RRAM as an analog neuromorphic synapse, Part I: Al/Mo/Pr0.7Ca0.3MnO3 material improvements and device measurements
- K. Moon
- Alessandro Fumarola
- et al.
- 2018
- IEEE J-EDS
PaperBidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part II: Impact of Al/Mo/Pr0.7Ca0.3MnO3 Device Characteristics on Neural Network Training Accuracy
- Alessandro Fumarola
- S. Sidler
- et al.
- 2018
- IEEE J-EDS
Paper