Lamina: Low Overhead Wear Leveling for NVM with Bounded Tail

Abstract

Emerging non-volatile memory (NVM) has been considered as a promising candidate for the next generation memory architecture because of its excellent characteristics. However, the endurance of NVM is much lower than DRAM. Without additional wear management technology, its lifetime can be very short, which extremely limits the use of NVM. This paper observes that the tail wear with a very small percentage of extreme deviation significantly hurts the lifetime of NVM, which the existing methods do not effectively solve. We present Lamina to address the tail wear issue, in order to improve the lifetime of NVM. Lamina consists of two parts: bounded tail wear leveling (BTWL) and lightweight wear enhancement (LWE). BTWL is used to make the wear degree of all pages close to the average value and control the upper limit of tail wear. LWE improves the accuracy of BTWL by exploiting the locality to interpolate low-frequency sampling schemes in virtual memory space. Our experiments show that compared with the state-of-the-art methods, Lamina can significantly improve the lifetime of NVM with low overhead.