RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning
Adarsh Kumar Kosta,Malik Aqeel Anwar,Priyadarshini Panda,Arijit Raychowdhury,Kaushik Roy,Adarsh Kumar Kosta,Malik Aqeel Anwar,Priyadarshini Panda,Arijit Raychowdhury,Kaushik Roy
Present-day Deep Reinforcement Learning (RL) systems show great promise towards building intelligent agents surpassing human-level performance. However, the computational complexity associated with the underlying deep neural networks (DNNs) leads to power-hungry implementations. This makes deep RL systems unsuitable for deployment on resource-constrained edge devices. To address this challenge, we...
