Relax and don't Stop: Graph-aware Asynchronous SSSP
Paper i 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

Författare

Marco D'antonio

Queen's University Belfast

Kåre von Geijer

Göteborgs universitet

Chalmers, Data- och informationsteknik

Thai Son Mai

Queen's University Belfast

Philippas Tsigas

Göteborgs universitet

Chalmers, Data- och informationsteknik

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,

Anpassad datastruktursemantik för skalbar processering av data

Vetenskapsrådet (VR) (2021-05443), 2022-01-01 -- 2025-12-31.

Relaxed Semantics Across the Data Analytics Stack (RELAX)

Europeiska kommissionen (EU) (EC/H2020/101072456), 2023-03-01 -- 2027-02-28.

Ämneskategorier (SSIF 2025)

Datavetenskap (datalogi)

DOI

10.1145/3711708.3723446

Mer information

Senast uppdaterat

2025-06-27