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February 27, 20260 citationsOpen Access

SMaRTT: Sender-based Marked Rapidly-adapting Trimmed & Timed Transport

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TBTommaso BonatoAKAbdul KabbaniAGAhmad Ghalayini

Key Points

  • This research aims to introduce and evaluate SMaRTT, a new sender-based congestion control algorithm designed for AI workloads in datacenters.
  • Developed the SMaRTT algorithm as part of the UEC NSCC specification.
  • Integrated delay, ECN, and packet trimming into a state machine for effective congestion management.
  • Evaluated SMaRTT against existing algorithms such as Swift, RoCE, and MPRDMA.
  • SMaRTT outperforms existing datacenter congestion control algorithms by up to 50%.
  • Demonstrated improved fairness in managing network resources.
  • Validation of design choices made in the UEC standard.

Abstract

With the rapid growth of artificial intelligence (AI) workloads in datacenters, the Ultra Ethernet Consortium (UEC) has defined a new high-performance transport layer to deliver the required performance at scale. A core component of this new standard is the Network Signal-based Congestion Control (NSCC) algorithm. This paper presents SMaRTT, the algorithm that forms the basis of the UEC NSCC specification. SMaRTT is a sender-based congestion control algorithm that systematically combines delay, Explicit Congestion Notification (ECN), and optional packet trimming into a cohesive state machine for fast, fair and precise window adjustments with seamless multipath support. At its core lies the novel QuickAdapt algorithm that accurately estimates and rapidly adapts to available capacity. Our evaluation shows that SMaRTT outperforms existing datacenter congestion control algorithms like Swift, RoCE, and MPRDMA by up to 50% and provides superior fairness, validating the design choices made in the UEC standard.

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Cite This Study

Bonato et al. (2026) studied this question.

synapsesocial.com/papers/69a1355fed1d949a99abf319https://doi.org/10.3929/ethz-c-000792559
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