DQN based page allocation for ReRAM main memory

Benefiting from the characteristics of non-volatile, low leakage power consumption, high density, and good scalability, resistive random access memory (ReRAM) has been considered to replace DRAM as the main memory of embedded devices. However, ReRAM suffers from endurance issue that may lead to data failure. In this work, we take the endurance discrepancy of different ReRAM cells into consideration and proposed a Deep Q-Network (DQN) based page allocation scheme to evenly wear out ReRAM cells. We further embedded the proposed scheme in a real-time scenario and proved that it can effectively guarantee the deadline of each task. We have conducted a series of simulations and the results show that compared with the traditional page allocation scheme, our scheme prolongs the endurance time of ReRAM up to 118%.