Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor

Due to the distributed and asynchronous nature of neural computation through low-energy spikes, brain-inspired hardware systems offer high energy efficiency and massive parallelism. One such platform is the IBM TrueNorth neurosynaptic system. Recently, TrueNorth compatible representation learning al...

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Veröffentlicht in:	IEEE journal on emerging and selected topics in circuits and systems 2018-12, Vol.8 (4), p.782-795
Hauptverfasser:	Shrestha, Amar, Ahmed, Khadeer, Wang, Yanzhi, Widemann, David P., Moody, Adam T., Van Essen, Brian C., Qiu, Qinru
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Biological neural networks Brain Circuits Computer architecture Computer simulation Emulators Hardware Logic gates long short-term memory Machine learning Mapping MATHEMATICS AND COMPUTING Microprocessors Neural networks neuromorphic hardware Neuromorphics Recurrent neural networks Rounding Short term Spiking Spiking neural networks State of the art Synchronism Synchronization Tradeoffs Upper bounds Weight
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