# On Parallel External-Memory Bidirectional Search

arXiv: https://arxiv.org/abs/2412.21104 · HTML: https://mlsanity.com/paper/2412.21104/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 39 references that are in the map.
- First posted on arXiv 30 Dec 2024.

## Builds on (most cited first, 1 of 1)

- [Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions](https://mlsanity.com/paper/1703.03868/) (2017)

## Abstract (arXiv)

Parallelization and External Memory (PEM) techniques have significantly enhanced the capabilities of search algorithms when solving large-scale problems. Previous research on PEM has primarily centered on unidirectional algorithms, with only one publication on bidirectional PEM that focuses on the meet-in-the-middle (MM) algorithm. Building upon this foundation, this paper presents a framework that integrates both uni- and bi-directional best-first search algorithms into this framework. We then develop a PEM variant of the state-of-the-art bidirectional heuristic search (BiHS) algorithm BAE* (PEM-BAE*). As previous work on BiHS did not focus on scaling problem sizes, this work enables us to evaluate bidirectional algorithms on hard problems. Empirical evaluation shows that PEM-BAE* outperforms the PEM variants of A* and the MM algorithm, as well as a parallel variant of IDA*. These findings mark a significant milestone, revealing that bidirectional search algorithms clearly outperform unidirectional search algorithms across several domains, even when equipped with state-of-the-art heuristics.