RL-CC is an RDMA congestion control algorithm based on reinforcement learning. This repository contains a trained RL-CC neural network model and a script to distill it into an ensemble of decision trees using synthetic data. The RL-CC model was trained using a proprietary NVIDIA congestion control simulator and the synthetic data is designed to approximate the data distribution that is created when running the model within the simulator.
To distill the model:
1. pip install -r requirements.txt
2. python3 distill_network.py