In this work we have used self-supervised learning and abft as error detection mechanism to enable fault-tolerance and robust error detection mechanism.

This repositoy contains the model and software for low power FPGA DNN deploymend solutions presented in following paper.

    "Low-Voltage Energy Efficient Neural Inference by Leveraging Fault Detection Techniques", Mehdi Safarpour, ‪Mohammad Sabokrou , Tommy Zhongmin,  John Massingham,  Lei Xun,              Olli Silven.

Note Vivado HLS can automatically generates systolic array for GEMM.

Mnist.ipynb : Trains a deep network over MNSIT dataset + SLL for rotation prediction as the pre-text task and stores the weights in a file HLS : contain the model in form of C++