A 5.37-TSOPS/W Reconfigurable Neuron Array with Dual-mode Neurons and Asynchronous Synapses for Energy-Efficient Inference and Biological Neural Network Simulation
Author:
Affiliation:
1. Shanghai Jiao Tong University
2. National Tsing Hua University
Funder
National Key Research and Development Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10347557/10347908/10347993.pdf?arnumber=10347993
Reference10 articles.
1. Towards spike-based machine intelligence with neuromorphic computing
2. A 0.086-mm2 12.7-pJ/SOP 64k-synapse 256-neuron online-learning digital spiking neuromorphic processor in 28-nm CMOS;Frenkel;IEEE TBioCAS,2018
3. Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations
4. ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales
5. 33.1 A 74 TMACS/W CMOS-RRAM Neurosynaptic Core with Dynamically Reconfigurable Dataflow and In-situ Transposable Weights for Probabilistic Graphical Models
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