Ouroboros Wear Leveling for NVRAM Using Hierarchical Block Migration

Abstract

Emerging nonvolatile RAM (NVRAM) technologies have a limit on the number of writes that can be made to any cell, similar to the erasure limits in NAND Flash. This motivates the need for wear leveling techniques to distribute the writes evenly among the cells. Unlike NAND Flash, cells in NVRAM can be rewritten without the need for erasing the entire containing block, avoiding the issues of space reclamation and garbage collection, motivating alternate approaches to the problem. In this article, we propose a hierarchical wear-leveling model called Ouroboros wear leveling. Ouroboros uses a two-level strategy whereby frequent low-cost intraregion wear leveling at small granularity is combined with interregion wear leveling at a larger time interval and granularity. Ouroboros is a hybrid migration scheme that exploits correct demand predictions in making better wear-leveling decisions while using randomization to avoid wear-leveling attacks by deterministic access patterns. We also propose a way to optimize wear-leveling parameter settings to meet a target smoothness level under limited time and space overhead constraints for different memory architectures and trace characteristics. Several experiments are performed on synthetically generated memory traces with special characteristics, two block-level storage traces, and two memory-line-level memory traces. The results show that Ouroboros wear leveling can distribute writes smoothly across the whole NVRAM with no more than 0.2% space overhead and 0.52% time overhead for a 512GB memory.