Parse Concurrent Data Structures: BST as an Example

TL;DR

This paper introduces a formal model for designing and analyzing scalable concurrent data structures, exemplified by new binary search trees, demonstrating the model's effectiveness through empirical testing.

Contribution

It formalizes a practical analysis model for concurrent structures' speedup and provides guidelines for designing scalable data structures, validated by experimental results.

Findings

The model accurately predicts speedup in concurrent data structures.

Edge-cutting BSTs outperform traditional designs under various workloads.

Guidelines improve the scalability and performance of concurrent data structures.

Abstract

Designing concurrent data structures should follow some basic rules. By separating the algorithms into two phases, we present guidelines for scalable data structures, with a analysis model based on the Amadal's law. To the best of our knowledge, we are the first to formalize a practical model for measuring concurrent structures' speedup. We also build some edge-cutting BSTs following our principles, testing them under different workloads. The result provides compelling evidence to back the our guidelines, and shows that our theory is useful for reasoning the varied speedup.