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PIPQ: Strict Insert-Optimized Concurrent Priority Queue

Authors Olivia Grimes , Ahmed Hassan , Panagiota Fatourou , Roberto Palmieri

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ACM Subject Classification
  • Theory of computation → Data structures design and analysis
Keywords
  • Priority Queue
  • Concurrent Data Structures
  • Synchronization

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Abstract

This paper presents PIPQ, a strict and linearizable concurrent priority queue whose design differs from existing solutions in literature because it focuses on enabling parallelism of insert operations as opposed to accelerating delete-min operations, as traditionally done. In a nutshell, PIPQ’s structure includes two levels: the worker level and the leader level. The worker level provides per-thread data structures enabling fast and parallel insertions. The leader level contains the highest priority elements in the priority queue and can thus serve delete-min operations. Our evaluation, which includes an exploration of different data access patterns, operation mixes, runtime settings, and an integration into a graph-based application, shows that PIPQ outperforms competitors in a variety of cases, especially with insert-dominant workloads.

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Olivia Grimes, Ahmed Hassan, Panagiota Fatourou, and Roberto Palmieri. PIPQ: Strict Insert-Optimized Concurrent Priority Queue. In 39th International Symposium on Distributed Computing (DISC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 356, pp. 35:1-35:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.DISC.2025.35

Author Details

Olivia Grimes
  • Lehigh University, Bethlehem, PA, USA
Ahmed Hassan
  • Lehigh University, Bethlehem, PA, USA
Panagiota Fatourou
  • FORTH ICS, Heraklion, Greece
  • Department of Computer Science, University of Crete, Heraklion, Greece
Roberto Palmieri
  • Lehigh University, Bethlehem, PA, USA

Funding

This material is based upon work supported by the National Science Foundation under Grant No. CNS-2045976 and by the Greek Ministry of Education, Religious Affairs and Sports through the HARSH project (project no. YΠ3TA - 0560901), which is carried out within the framework of the National Recovery and Resilience Plan "Greece 2.0" with funding from the European Union - NextGenerationEU.

Acknowledgements

The authors would like to acknowledge Mike Spear for all his input, feedback, and support.

Supplementary Materials

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