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arXiv · 2401.07467

Selection Improvements on the Parallel Iterative Algorithm for Stable Matching

Scott Wynn·Alec Kyritsis·Stephora Alberi·Enyue Lu
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Abstract

Sequential algorithms for the Stable Matching Problem are often too slow in the context of some large scale applications like switch scheduling. Parallel architectures can offer a notable decrease in runtime complexity. We propose a stable matching algorithm using $n^2$ processors that converges in $O(n log(n))$ average runtime. The algorithm is structurally based on the Parallel Iterative Improvement (PII) algorithm, where we improve the convergence rate from $90\%$ to $100\%$ over a large number of trials. We suggest alternative selection methods for pairs in the PII algorithm, called Right-Minimum and Dynamic Selection, as well as a faster preprocessing step, called Quick Initialization, resulting in full convergence over $3.6$ million trials and significantly improved runtime.

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Scott Wynn, Alec Kyritsis, Stephora Alberi, Enyue Lu. 2024-01-15. Selection Improvements on the Parallel Iterative Algorithm for Stable Matching. https://arxiv.org/abs/2401.07467

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