Enabling Reconfiguration-Communication Overlap for Collective Communication in Optical Networks Article Swipe

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Zhuolong Yu , Gongming Zhao , Hongli Xu ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2510.19322

Collective communication (CC) is widely adopted for large-scale distributed machine learning (DML) training workloads. DML's predictable traffic pattern provides a great oppotunity for applying optical network technology. Existing optical interconnects-based CC schemes adopt ``one-shot network reconfiguration'', which provisions static high-capacity topologies for an entire collective operation -- sometimes for a full training iteration. However, this approach faces significant scalability limitations when supporting more complex and efficient CC algorithms required for modern workloads: the ``one-shot'' strategies either demand excessive resource overprovisioning or suffer performance degradation due to rigid resource allocation. To address these challenges, we propose SWOT, a demand-aware optical network framework. SWOT employs ``intra-collective reconfiguration'' and can dynamically align network resources with CC traffic patterns. SWOT incorporates a novel scheduling technique that overlaps optical switch reconfigurations with ongoing transmissions, and improves communication efficiency. SWOT introduce a lightweight collective communication shim that enables coordinated optical network configuration and transmission scheduling while supporting seamless integration with existing CC libraries. Our simulation results demonstrate SWOT's significant performance improvements.

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Type: preprint
Landing Page: http://arxiv.org/abs/2510.19322
PDF: https://arxiv.org/pdf/2510.19322
OA Status: green
OpenAlex ID: https://openalex.org/W4416246754

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DOI: https://doi.org/10.48550/arxiv.2510.19322

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Title: Enabling Reconfiguration-Communication Overlap for Collective Communication in Optical Networks

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Type: preprint

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Publication year: 2025

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Publication date: 2025-10-22

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Authors: Zhuolong Yu, Gongming Zhao, Hongli Xu

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Landing page: https://arxiv.org/abs/2510.19322

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PDF URL: https://arxiv.org/pdf/2510.19322

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