activity
20162026
most citedUnikraft: Fast, Specialized Unikernels the Easy Way

109 citations · 116 across the 13 of their papers we have counts for

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9 papers · 1 filter

cs.NI2026

Understanding the oversubscription behaviour of DragonFly+ networks

Vlad-Adrian Ulmeanu, Costin Raiciu, Iulian-Ilie Drăcea

The Max-Host Dragonfly+ topology's original paper proves that there is a 2:1 worst-case oversubscription ratio in expectation for the permutation traffic pattern. We show that the…

cs.NI2026

SlimTCP: It's fast, but not because it's slim

Mihai Drosi Caju, Costin Raiciu

In this paper, the authors explore the possibility of improving the performance of TCP/IP stacks in the context of data-center networks. This paper will focus particularly on the c…

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.NI2026★ 2 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.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…

cs.NI2025★ 1 cited

An Extensible Software Transport Layer for GPU Networking

Yang Zhou, Zhongjie Chen, Ziming Mao +11

Fast-evolving machine learning (ML) workloads have increasing requirements for networking. However, host network transport on RDMA NICs is hard to evolve, causing problems for ML w…