Sky$^\epsilon$-Tree: Embracing the Batch Updates of B$^\epsilon$-trees through Access Port Parallelism on Skyrmion Racetrack Memory

TL;DR

The paper introduces Skyε-tree, a novel data structure optimized for skyrmion racetrack memory, leveraging access port parallelism to improve batch update handling, query, and insert performance while reducing energy consumption.

Contribution

It proposes Skyε-tree, a new variant of Bε-trees tailored for SK-RM, addressing batch update challenges and exploiting access port parallelism for enhanced performance.

Findings

Significant improvements in access performance.

Reduced energy consumption.

Effective handling of batch updates in SK-RM.

Abstract

Owing to the characteristics of high density and unlimited write cycles, skyrmion racetrack memory (SK-RM) has demonstrated great potential as either the next-generation main memory or the last-level cache of processors with non-volatility. Nevertheless, the distinct skyrmion manipulations, such as injecting and shifting, demand a fundamental change in widely-used memory structures to avoid excessive energy and performance overhead. For instance, while B{\epsilon}-trees yield an excellent query and insert performance trade-off between B-trees and Log-Structured Merge (LSM)-trees, the applicability of deploying B{\epsilon}-trees onto SK-RM receives much less attention. In addition, even though optimizing designs have been proposed for B+-trees on SK-RM, those designs are not directly applicable to B{\epsilon}-trees owing to the batch update behaviors between tree nodes of B{\epsilon}-trees. Such an observation motivates us to propose the concept of Sky{\epsilon}-tree to effectively utilize the access port parallelism of SK-RM to embrace the excellent query and insert performance of B{\epsilon}-trees. Experimental results have shown promising improvements in access performance and energy conservation.