most citedResilient AI Supercomputer Networking using MRC and SRv6

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

hep-ex2026

Probing Nuclear Effects with Transverse Kinematic Imbalance in Muon-neutrino Induced Charged-Current Production on Argon with the MicroBooNE Detector

MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana +192

Neutrino-nucleus cross-section measurements are needed to improve interaction modeling and to enable precision neutrino oscillation measurements in upcoming experiments such as the…

cs.NI2026

The Multipath Reliable Connection (MRC) Transport

Rip Sohan, Eric Spada, Eric Davis +36

MRC is an open, production-grade transport designed for large-scale AI/ML training over best-effort Ethernet. It extends RoCEv2 with explicit, composable primitives for per-packet…

cs.NI20262 cited

Resilient AI Supercomputer Networking using MRC and SRv6

Joao Araujo, Alex Chow, Mark Handley +47

Tail latency dominates the performance of synchronous pretraining jobs when running at very large scales. We describe a three-pronged approach: (1) a new RDMA-based transport proto…

cs.NI2026

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

Tommaso Bonato, Abdul Kabbani, Ahmad Ghalayini +10

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 th…

cs.NI2025

Ultra Ethernet's Design Principles and Architectural Innovations

Torsten Hoefler, Karen Schramm, Eric Spada +13

The recently released Ultra Ethernet (UE) 1.0 specification defines a transformative High-Performance Ethernet standard for future Artificial Intelligence (AI) and High-Performance…