11 citations · 23 across the 8 of their papers we have counts for
5 papers · 1 filter
PCM: Programmable Congestion Management for Terabit RDMA NICs
Mikhail Khalilov, Timo Schneider, Tommaso Bonato +10
Datacenter congestion control (CC) and load balancing (LB) evolve rapidly as workload demands change, but deployment depends on RDMA hardware and transport interfaces. Emerging pro…
Scalable Packet Tracking on FPGAs for Erasure-Coded RDMA over Lossy WANs
Yicheng Qian, Konstantin Taranov, Yevgeny Yankilevich +5
Modern AI workloads increasingly rely on scale across architectures that interconnect multiple datacenters to form a single "AI factory", overcoming the power and cooling constrain…
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…
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…
In-Network Collective Operations: Game Changer or Challenge for AI Workloads?
Torsten Hoefler, Mikhail Khalilov, Josiah Clark +9
This paper summarizes the opportunities of in-network collective operations (INC) for accelerated collective operations in AI workloads. We provide sufficient detail to make this i…