Our paper “Accelerating Proximal Policy Optimization on CPU-FPGA Heterogeneous Platforms” has been accepted as a full paper at the 28th IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM ‘20). This paper describes a high-throughput architectural design for the Deep Reinforcement Learning algorithm — PPO acceleration on CPU-FPGA heterogeneous platform.
