Fast Parallel Operations on Search Trees

TL;DR

This paper introduces efficient parallel algorithms for fundamental search tree operations like split, join, and set operations, achieving logarithmic latency and optimal work, with practical implementations outperforming previous methods.

Contribution

It presents both theoretically optimal and practical parallel algorithms for search tree operations, improving speed and efficiency over prior work.

Findings

Parallel split achieves logarithmic latency.

Parallel join and set operations are also logarithmic and optimal.

Practical implementations are several times faster than previous methods.

Abstract

Using (a,b)-trees as an example, we show how to perform a parallel split with logarithmic latency and parallel join, bulk updates, intersection, union (or merge), and (symmetric) set difference with logarithmic latency and with information theoretically optimal work. We present both asymptotically optimal solutions and simplified versions that perform well in practice - they are several times faster than previous implementations.