Enhanced Wear-Rate Leveling for PRAM Lifetime Improvement Considering Process Variation

Abstract

The limited write endurance is one of the major obstacles for phase-change random access memory (PRAM)-based main memory. Traditionally, wear-leveling (WL) techniques were proposed to enhance its lifetime by balancing write traffic. However, these techniques do not concern the endurance variation in PRAM chips. When different PRAM cells have distinct endurance, balanced writes results in lifetime degradation due to the weakest cells. In this paper, we first define a new metric-wear rate (i.e., writes/endurance) considering both the write traffic and endurance distribution from application and hardware, respectively. After investigating the writing behavior of applications and endurance variation, we propose an architecture-level leveling mechanism to balance wear rate of cells across the PRAM chip. Hardware and algorithm to support the proposed leveling mechanism are presented. Moreover, there is an important tradeoff between endurance improvement and swapping data volume. To co-optimize endurance and swapping, this situation is formulated as a maximum weight perfect matching problem in bipartite graph. Thereafter, a novel algorithm that minimizes wear-rate and swapping by employing Kuhn–Munkras algorithm is proposed to maximize PRAM lifetime and minimize performance degradation. The experimental results show $\sim 17 \times $ lifetime improvement over prior WL.