This repository contains the System-Verilog source files describing a HW fully-combinational BNN model.

• src\ includes the HDL description of basic BNN building blocks (spatial convolutional and fully-connected layers)
• test\ contains multiple example of network models
• src\ includes network-specific HDL descriptions. Among them, weights.sv contains the networks parameters.
• tb\ inlcudes the testbench files for running simulation.
• sim\ used for simulation purpose with ModelSim (tested with version 10.6b)

Simply navigate to the sim\ folder of the desidered netowork example and type

make clean build run

for sythesis and simulation. Stimulus is defined in tb/data.sv.

Sythensis results with GF22 SOI technology are reported in the paper. Please, acknowledge it if you make use of our code.

Rusci, Manuele, Lukas Cavigelli, and Luca Benini. 
"Design Automation for Binarized  Neural Networks: A Quantum Leap Opportunity?." 
Circuits and Systems (ISCAS), 2018 IEEE International Symposium on. IEEE, 2018.