WoLFRaM: Enhancing Wear-Leveling and Fault Tolerance in Resistive Memories using Programmable Address Decoders

TL;DR

WoLFRaM is a novel mechanism that uses programmable address decoders to simultaneously improve wear-leveling and fault tolerance in resistive memories, significantly extending their lifetime with minimal performance and energy overheads.

Contribution

It introduces a low-cost, integrated approach combining wear-leveling and fault tolerance using programmable resistive address decoders in resistive memories.

Findings

Memory lifetime increased by 68% with WoLFRaM.

Performance overhead is only 0.51% on average.

Energy overhead is approximately 0.47%.

Abstract

Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate endurance-related memory failures are 1) wear-leveling, to evenly distribute the writes across the entire memory, and 2) fault tolerance, to correct memory cell failures. However, one of the main open challenges in extending the lifetime of existing resistive memories is to make both techniques work together seamlessly and efficiently. To address this challenge, we propose WoLFRaM, a new mechanism that combines both wear-leveling and fault tolerance techniques at low cost by using a programmable resistive address decoder (PRAD). The key idea of WoLFRaM is to use PRAD for implementing 1) a new efficient wear-leveling mechanism that remaps write accesses to random physical locations on the fly, and 2) a new efficient fault tolerance mechanism that recovers from faults by remapping failed memory blocks to available physical locations. Our evaluations show that, for a Phase Change Memory (PCM) based system with cell endurance of 108 writes, WoLFRaM increases the memory lifetime by 68% compared to a baseline that implements the best state-of-the-art wear-leveling and fault correction mechanisms. WoLFRaM's average / worst-case performance and energy overheads are 0.51% / 3.8% and 0.47% / 2.1% respectively.