Parallel Point-to-Point Shortest Paths and Batch Queries

We propose Orionet, efficient parallel implementations of Point-to-Point Shortest Paths (PPSP) queries using bidirectional search (BiDS) and other heuristics, with an additional focus on batch PPSP queries. We present a framework for parallel PPSP built on existing single-source shortest paths (SSSP) frameworks by incorporating novel pruning conditions. As a result, we develop efficient parallel PPSP algorithms based on early termination, bidirectional search, A* search, and bidirectional A*---all with simple and efficient implementations.

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Publication Details

Published
2025-07-16
DOI
https://doi.org/10.1145/3694906.3743311
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Parallel Point-to-Point Shortest Paths and Batch Queries

Yihan Sun, Andric Li, Yan Gu, Xiaojun Dong
Data Management and Algorithms
article

Parallel Point-to-Point Shortest Paths and Batch Queries

Yihan Sun, Andric Li, Yan Gu, Xiaojun Dong
article en

Abstract

We propose Orionet, efficient parallel implementations of Point-to-Point Shortest Paths (PPSP) queries using bidirectional search (BiDS) and other heuristics, with an additional focus on batch PPSP queries. We present a framework for parallel PPSP built on existing single-source shortest paths (SSSP) frameworks by incorporating novel pruning conditions. As a result, we develop efficient parallel PPSP algorithms based on early termination, bidirectional search, A* search, and bidirectional A*---all with simple and efficient implementations.

University of California, Riverside (US)
National Science Foundation
Openalex Percentile: Top 79%
Data Management and Algorithms
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