Improvement of State Stability in Multi-Level Resistive Random-Access Memory (RRAM) Array for Neuromorphic Computing

In this work, a new operation scheme is developed to improve the state stability of multi-level resistive random-access memory (RRAM) array. We found that the state instability after programming is mainly derived from the excessive oxygen vacancies generated by the abrupt SET process. Based on the understanding of the state stability after operation, triangular pulse is adopted for the programming of multi-level RRAM, which can effectively suppress the short-term relaxation and improve the long-time retention. Comparison results show that the degradation on recognition accuracy of Cifar-10 over time in ResNet18 network reduces from 8.07% by using square pulse programming to 0.93% by utilizing the proposed operation scheme.