331 citations · 862 across the 12 of their papers we have counts for
3 papers · 2 filters
THOR -- A Neuromorphic Processor with 7.29G TSOP/mmJs Energy-Throughput Efficiency
Mayank Senapati, Manil Dev Gomony, Sherif Eissa +2
Neuromorphic computing using biologically inspired Spiking Neural Networks (SNNs) is a promising solution to meet Energy-Throughput (ET) efficiency needed for edge computing device…
ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales
Charlotte Frenkel, Giacomo Indiveri
A robust real-world deployment of autonomous edge devices requires on-chip adaptation to user-, environment- and task-induced variability. Due to on-chip memory constraints, prior…
Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions
Arindam Basu, Charlotte Frenkel, Lei Deng +1
In this paper, we reviewed Spiking neural network (SNN) integrated circuit designs and analyzed the trends among mixed-signal cores, fully digital cores and large-scale, multi-core…