Impact Of Process Variation On Endurance Algorithms For Wear-Prone Memories

Non-volatile memories, such as Flash and Phase-Change Memory, are replacing other memory and storage technologies. Although these new technologies have desirable energy and scalability properties, they are prone to wear-out due to excessive write operations. Because wear-out is an important phenomenon, a number of endurance management schemes have been proposed. There is a trade-off between what techniques to use, depending on the range of bit cell lifetime within a device. This range in cell durability arises from effects due to process variation. In this paper, we describe modeling techniques to analyze trade-offs for endurance management based on the anticipated distribution of cell lifetime. This analysis considers two general endurance strategies (physical capacity degradation and physical sparing) under four distributions of cell lifetime (constant, linear, normal, and bimodal). The modeling techniques can be used to determine how much redundancy is needed when a sparing endurance strategy is adopted. With the correct choice of technique, the device lifetime can be doubled.