Ouroboros Wear-leveling: A Two-level Hierarchical Wear-leveling Model for NVRAM

Emerging non-volatile 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. We propose a novel hierarchical wearleveling model called Ouroboros Wear-leveling. Ouroboros uses a two-level strategy whereby frequent low-cost intra-region wearleveling is combined with predictive inter-region wear-leveling at a larger time interval and spatial 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. Several experiments are performed on both specially crafted memory traces and two block-level storage traces generated by Microsoft and FIU. The results show that Ouroboros Wear-leveling can successfully distribute writes smoothly across the whole NVRAM with very small space and time overheads for a 512 GB memory.

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