Framework Reconfigurability

[amir-ghz]

I've come across your paper titled "DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-chip Training" seeking analytical tools for DNNs. My question is, can this framework be extended for customized neural network models and architectures (like LSTMs) that you did not list in your paper? And is there an option for voltage scaling in your framework? Many thanks in advance.