zwhexplorer/Spiking-Neural-Network-Accelerator-EE552-project

Spiking Neural Network Accelerator

29
/ 100
Experimental

This project helps chip designers understand and implement machine learning accelerators inspired by spiking neural networks like TrueNorth and Loihi. It takes architectural and circuit design principles as input, and outputs models and implementations of asynchronous spiking neural networks, particularly focusing on how traditional convolutional neural networks can be mapped to them. This is primarily for students and professionals in electrical engineering or computer architecture.

No commits in the last 6 months.

Use this if you are a chip designer or electrical engineering student interested in modeling and implementing asynchronous spiking neural network accelerators for machine learning.

Not ideal if you are looking for a ready-to-use software library or a high-level tool for general machine learning application development.

chip-design neuromorphic-computing VLSI-design computer-architecture asynchronous-circuits
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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15

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4

Language

SystemVerilog

License

Last pushed

May 18, 2022

Commits (30d)

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