About the Project
The repository contains some examples of pre-trained SNN (Spiking Neural Network) models.
The project has been tested under the Linux Ubuntu 16.04 LTS with CUDA 9.0.
- Linux (We have tested under ubuntu 16.04)
- CUDA 9.0 (Using other CUDA verions may not work)
Download this project
git clone [email protected]:etri/nest-snn.git
Patch modified CARLsim4 source code
cd CARLsim4 patch -p1 < carlsim.patch
(Note) The neuron and synapse models assumed in MM-BP differ from those provided by CARLsim4. So, we additionally implemented the neuron and synapse models in CARLsim4. And we provide the additional implementation in the form of patch file(carlsim.patch) upon request. Please contact us if you would like to use the patch file.
Install CARLsim4 following the CARLsim4 installation process.
cd snn_models/MNIST_trained make ./trained_mnist
cd snn_models/N-MNIST_trained make ./trained_nmnist
cd snn_models/TI46_trained make ./trained_ti46
Get the MNIST dataset. Place the dataset in the snn_models/MNIST_trained/mnist.
We provide some input samples(snn_models/N-MNIST_trained/sample_inputs) for the test.
TI 46 dataset is not free, and the source code used for encoding has not been opened. Thus we do not provide input files. If you contact us via email, we can guide you on how to obtain the dataset and how to encode it.
This project is licensed under Apache 2.0 License.
PAK,EUNJI - [email protected]
Project Link: https://github.com/etri/nest-snn.git