A Heuristic Algorithm for Shortest Path Search
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916809306800128 |
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| author | Yu, Huashan Wang, Xiaolin Luo, Yingwei |
| author_facet | Yu, Huashan Wang, Xiaolin Luo, Yingwei |
| contents | The Single-Source Shortest Path (SSSP) problem is well-known for the challenges in developing fast, practical, and work-efficient parallel algorithms. This work introduces a novel shortest path search method. It allows paths with different lengths to be extended in parallel at the cost of almost negligible repeated relaxations. A dynamic-stepping heuristic is proposed for the method to efficiently reduce the extended paths and the synchronizations. A traversal-optimization heuristic is proposed to improve the method by efficiently reducing the created paths and alleviating the load imbalance. Based on the method, the two heuristics are used to develop a practical SSSP algorithm, which tactfully reduces workload and overhead. The heuristics and the algorithm were evaluated on 73 real-world and synthetic graphs. The algorithm was also compared with five state-of-the-art SSSP implementations. On each GAP benchmark suite graph except Road, its speedup to the best achieved by these five implementations is 2.5x to 5.83x. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_19349 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Heuristic Algorithm for Shortest Path Search Yu, Huashan Wang, Xiaolin Luo, Yingwei Distributed, Parallel, and Cluster Computing The Single-Source Shortest Path (SSSP) problem is well-known for the challenges in developing fast, practical, and work-efficient parallel algorithms. This work introduces a novel shortest path search method. It allows paths with different lengths to be extended in parallel at the cost of almost negligible repeated relaxations. A dynamic-stepping heuristic is proposed for the method to efficiently reduce the extended paths and the synchronizations. A traversal-optimization heuristic is proposed to improve the method by efficiently reducing the created paths and alleviating the load imbalance. Based on the method, the two heuristics are used to develop a practical SSSP algorithm, which tactfully reduces workload and overhead. The heuristics and the algorithm were evaluated on 73 real-world and synthetic graphs. The algorithm was also compared with five state-of-the-art SSSP implementations. On each GAP benchmark suite graph except Road, its speedup to the best achieved by these five implementations is 2.5x to 5.83x. |
| title | A Heuristic Algorithm for Shortest Path Search |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2506.19349 |