A Low-Cost Reliable Racetrack Cache Based on Data Compression

TL;DR

This paper introduces a low-cost, reliable racetrack cache design that leverages data compression and strong ECCs to significantly improve fault tolerance and longevity of NVM-based caches, especially RTM, with minimal overhead.

Contribution

It proposes a novel cache scheme combining data compression and ECC redundancy to enhance RTM reliability without substantial hardware or performance costs.

Findings

Increases cache mean-time-to-failure by 11.3x on average.

Achieves this reliability improvement with less than 1% overhead.

Effectively tolerates multiple-bit errors in RTM cache blocks.

Abstract

SRAM-based cache memory faces several scalability limitations in deep nanoscale technologies, e.g., high leakage current, low cell stability, and low density. Emerging Non-Volatile Memory (NVM) technologies have received lots of attention in recent years, where Racetrack Memory (RTM) is among the most promising ones. RTM has the highest density among all NVMs and its access performance is comparable to SRAM technology. Therefore, RTM is a suitable alternative for SRAM in the Last-Level Caches (LLCs). Despite all its benefits, RTM confronts different reliability challenges due to the stochastic behavior of its storage element and highly error-prone data shifting, leading to a high probability of multiple-bit errors. Conventional Error-Correcting Codes (ECCs) are either incapable of tolerating multiple-bit errors or require a large amount of extra storage for check bits. This paper proposes taking advantage of value locality for compressing data blocks and freeing up a large fraction of cache blocks for storing data redundancy of strong ECCs. Utilizing the proposed scheme, a large majority of cache blocks are protected by strong ECCs to tolerate multiple-bit errors without any storage overhead. The evaluation using gem5 full-system simulator demonstrates that the proposed scheme enhances the mean-time-to-failure of the cache by an average of 11.3x with less than 1% hardware and performance overhead.