I am interested in a graph generation through machine learning or some other method.
Hardware consists of wire and transistor and these compose a graph as logic circuit. I want to try to generate neural network hardware described in hardware description language (HDL), from network model description such as using PyTorch, TensorFlow, etc.
There is infrastructure of NNVM and TVM for example to generate program for specific hardwares. Recently they challenge to develop Verilog-HDL generation.
Silicon chip is not capable for entire neural network graph consisting of billion of nodes and edges, so partitioning and scheduling are necessary for the set of such the fragments.
I think graph neural network can work for these, I expect to detect similarity of sub graph pattern (fragments).
Or, neural network architecture search is one of hot topics, so its technique can be applied to my hardware architecture search domain.
Any suggestions are welcome.
Thanks and Regards,