Relax and don't Stop: Graph-aware Asynchronous SSSP
Paper in proceeding, 2025

The Parallel Single-Source Shortest Path (SSSP) problem has been tackled through many implementations, yet no single approach consistently outperforms others across diverse graph structures. Moreover, most implementations require extensive parameter tuning to reach peak performance. In this paper, we introduce the AdaMW scheduler, which dynamically selects between the schedulers Wasp and Multi-Queue. To achieve this, we use graph sampling and heuristics to select and configure the scheduler. In contrast to common state-of-the-art bulk-synchronous implementations, AdaMW is fully asynchronous, thus not needing to stop for global barriers. The resulting scheduler is highly competitive with the best manually-tuned, state-of-the-art implementations.

asynchrony

shared-memory

shortest path

priority scheduler

Author

Marco D'antonio

Queen's University Belfast

Kåre von Geijer

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers)

Thai Son Mai

Queen's University Belfast

Philippas Tsigas

University of Gothenburg

Chalmers, Computer Science and Engineering (Chalmers)

Hans Vandierendonck

Queen's University Belfast

Proceedings of the 1st Fastcode Programming Challenge Fcpc 2025

43-47
9798400714467 (ISBN)

1st FastCode Programming Challenge, FCPC 2025
Las Vegas, USA,

Relaxed Concurrent Data Structure Semantics for Scalable Data Processing

Swedish Research Council (VR) (2021-05443), 2022-01-01 -- 2025-12-31.

Relaxed Semantics Across the Data Analytics Stack (RELAX)

European Commission (EC) (EC/H2020/101072456), 2023-03-01 -- 2027-02-28.

Subject Categories (SSIF 2025)

Computer Sciences

DOI

10.1145/3711708.3723446

More information

Latest update

6/27/2025