FireFly v2: Advancing Hardware Support for High-Performance Spiking Neural Network With a Spatiotemporal FPGA Accelerator-Reference-Cited by-同舟云学术

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FireFly v2: Advancing Hardware Support for High-Performance Spiking Neural Network With a Spatiotemporal FPGA Accelerator

Published:2024-09 Issue:9 Volume:43 Page:2647-2660
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Li Jindong¹^ORCID,Shen Guobin²^ORCID,Zhao Dongcheng³^ORCID,Zhang Qian¹^ORCID,Zeng Yi³^ORCID

Affiliation:

1. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China

2. School of Future Technology, University of Chinese Academy of Sciences, Beijing, China

3. Brain-Inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

Chinese Academy of Sciences Foundation Frontier Scientific Research Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/43/10643378/10478105.pdf?arnumber=10478105

Reference32 articles.

1. Networks of spiking neurons: The third generation of neural network models

2. Backpropagation with biologically plausible spatiotemporal adjustment for training deep spiking neural networks

3. Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

4. SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation

5. DIET-SNN: A Low-Latency Spiking Neural Network With Direct Input Encoding and Leakage and Threshold Optimization

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