Experimental demonstration and tolerancing of a large-scale neural network (165,000 synapses), using phase-change memory as the synaptic weight element
- Geoffrey W. Burr
- Robert M. Shelby
- et al.
- 2014
- IEDM 2014
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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8 results for Carmelo Di Nolfo
Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Comparative performance analysis (accuracy, speed, and power)
- Geoffrey W. Burr
- Pritish Narayanan
- et al.
- 2015
- IEDM 2015
Equivalent-accuracy accelerated neural-network training using analogue memory
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2018
- Nature
Convolutional networks for fast, energy-efficient neuromorphic computing
- Steven K. Esser
- Paul Merolla
- et al.
- 2016
- PNAS
A low power, fully event-based gesture recognition system
- Arnon Amir
- Brian Taba
- et al.
- 2017
- CVPR 2017
Improved deep neural network hardware-Accelerators based on non-volatile-memory: The local gains technique
- Irem Boybat
- Carmelo Di Nolfo
- et al.
- 2017
- ICRC 2017
Non-volatile memory as hardware synapse in neuromorphic computing: A first look at reliability issues
- Robert M. Shelby
- Geoffrey W. Burr
- et al.
- 2015
- IRPS 2015
Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element
- Geoffrey W. Burr
- Robert M. Shelby
- et al.
- 2015
- IEEE T-ED