[Paper] Engineering Scalable Distributed List Ranking

Source: arXiv - 2606.09318v1

Overview

The list ranking problem is one of the classical problems of parallel computing, with nontrivial algorithms and many applications as a subroutine for solving other problems. While it has been intensively studied in the early days of parallel computing, few things happened in the last 20 years. In particular, there is little work on scaling list ranking to large machines and input sizes. We reconsider list ranking starting from the ground-breaking results of Sibeyn a quarter century ago. We employ algorithm and performance engineering to improve his sparse ruling-set algorithm, making it capable of scaling to many processors, and provide a more detailed analysis of the impact of the algorithm’s parameters, further guiding our practical implementation. We perform an extensive experimental study across a variety of input instances with different structural properties. We demonstrate that indirect communication, exploiting input locality, and message coalescing allows scaling to billions of elements on up to 24,576 cores.

Key Contributions

This paper presents research in the following areas:

• cs.DC
• cs.DS

Methodology

Please refer to the full paper for detailed methodology.

Practical Implications

This research contributes to the advancement of cs.DC.

Authors

• Peter Sanders
• Matthias Schimek
• Tim Niklas Uhl
• Thomas Weidmann

Paper Information

• arXiv ID: 2606.09318v1
• Categories: cs.DC, cs.DS
• Published: June 8, 2026
• PDF: Download PDF