{"ID":2858084,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.08072","arxiv_id":"2510.08072","title":"When Light Bends to the Collective Will: A Theory and Vision for Adaptive Photonic Scale-up Domains","abstract":"As chip-to-chip silicon photonics gain traction for their bandwidth and energy efficiency, collective communication has emerged as a critical bottleneck in scale-up systems. Programmable photonic interconnects offer a promising path forward: by dynamically reconfiguring the fabric, they can establish direct, high-bandwidth optical paths between communicating endpoints -- \\emph{synchronously and guided by the structure of collective operations} (e.g., AllReduce). However, realizing this vision -- \\emph{when light bends to the collective will} -- requires navigating a fundamental trade-off between reconfiguration delay and the performance gains of adaptive topologies. In this paper, we present a simple theoretical framework for adaptive photonic scale-up domains that makes this trade-off explicit and clarifies when reconfiguration is worthwhile. Along the way, we highlight a connection -- not surprising but still powerful -- between the Birkhoff--von Neumann (BvN) decomposition, maximum concurrent flow (a classic measure of network throughput), and the well-known $α$-$β$ cost model for collectives. Finally, we outline a research agenda in algorithm design and systems integration that can build on this foundation.","short_abstract":"As chip-to-chip silicon photonics gain traction for their bandwidth and energy efficiency, collective communication has emerged as a critical bottleneck in scale-up systems. Programmable photonic interconnects offer a promising path forward: by dynamically reconfiguring the fabric, they can establish direct, high-bandw...","url_abs":"https://arxiv.org/abs/2510.08072","url_pdf":"https://arxiv.org/pdf/2510.08072v1","authors":"[\"Vamsi Addanki\"]","published":"2025-10-09T10:59:27Z","proceeding":"cs.NI","tasks":"[\"cs.NI\",\"cs.DC\"]","methods":"[]","has_code":false}