117 citations · 119 across the 3 of their papers we have counts for
3 papers
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.DC2019★ 117 cited
Scaling Distributed Machine Learning with In-Network Aggregation
Amedeo Sapio, Marco Canini, Chen-Yu Ho +7
Training machine learning models in parallel is an increasingly important workload. We accelerate distributed parallel training by designing a communication primitive that uses a p…