Application of Deep Reinforcement Learning to Dynamic Verification of DRAM Designs

This paper presents a deep neural network based test vector generation method for dynamic verification of memory devices. The proposed method is built on reinforcement learning framework, where the action is input stimulus on device pins and the reward is coverage score of target circuitry. The developed agent efficiently explores high-dimensional and large action space by using policy gradient me...