State Asymmetry Driven State Remapping in Phase Change Memory

Abstract

Phase change memory (PCM) is one of the most promising candidates to replace DRAM as main memory in deep submicron regime. Regardless of single-level or multiple-level cells, the programming costs to each state exhibit significant asymmetries in latency, energy and endurance. In this paper, we exploit the potential of reducing programming costs in terms of latency, energy, and endurance for PCM through state remapping. First, quantitative programming models are constructed for cost assessments. Then, both dynamic and static remapping schemes are analyzed and compared. The observation that the efficacy of dynamic state remappings is instable motivates us to propose a static remapping technique, which outperforms previous work in cost reduction within much lower implementation overhead. The optimality of the proposed static state remapping is also proved. The evaluation results confirm the efficacy of the proposed state remapping technique in delivering a stable and promising cost reduction in latency, energy, and wear.