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May 18th, 2021, 4:23am
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Machine-Learning-based-Behavioral Modelling (Read 69 times)
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Machine-Learning-based-Behavioral Modelling
Apr 19th, 2021, 6:33am

I need your help in debugging/tips to debug a Verilog-A module that I created based on the training of a Recurrent Neural Network (RNN).

The model is supposed to solve the non-linear differential system of equations coming from the RNN representation.

I will summarize everything in steps so that it will be easier to discuss it afterward.

1. I created a testbench for a chain of inverters and got the data (Vin,Iout) in .csv format after interpolation to a timestep=1e-9 s.

Attached testbench:
and sample of Iout:
and training_data.csv:

2.Train/test datasets are pre-processed (scaled/normalized/standardized ...) to fit the RNN model used.
After tuning model parameters, itís tested against unseen stimuli.

Attached learning curves:
RNN prediction:
and parameters matrices:

3. The parameter arrays are flattened to be used as 1-D vectors in the Verilog-A module (since multi-D is not allowed in Verilog-A)

Below, you will find a listing of my code which is basically using Spectre to solve the continuous non-linear system of equations of the RNN model.


*** attached summary for the equations and the equivalent circuit of the model.

4. results after compiling and running the simulation look like that:

which is not really good! I changed alpha to consider different simulation steps but this is the best result.

Sorry for the long post and the many links and thanks in advance to your time.
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