RoCE vs InfiniBand for AI clusters

What RoCE and InfiniBand are

RoCE is RDMA over Converged Ethernet; the version that matters for AI is RoCEv2, which encapsulates RDMA in UDP/IP on destination port 4791 so the traffic is routable across a Layer 3 Ethernet fabric. RDMA lets GPUs and storage move data directly between memory with low latency and low CPU overhead. Because RoCEv2 rides on standard Ethernet, its switches, NICs, optics, and tooling come from many vendors and share one operational model with the rest of the data center.

InfiniBand is a purpose-built interconnect from the InfiniBand Trade Association, designed from the start for low-latency, lossless RDMA with its own switches, host channel adapters, cabling, and a centralized subnet manager. It is lossless by architecture: credit-based flow control means a sender transmits only when the receiver has advertised buffer credits, so the fabric does not drop under congestion. For two decades that design gave InfiniBand a real edge for tightly coupled HPC.

The practical question for an AI cluster is no longer which is technically purer, but which transport meets the workload while keeping cost, supply chain, and operations sane. The table below lays out the axes that decide it.

RoCE vs InfiniBand at a glance

InfiniBand is a trademark of the InfiniBand Trade Association. NVIDIA and Mellanox are trademarks of their respective owners. This comparison is provided for informational purposes and does not imply affiliation or endorsement.

各自的制胜场景

Why many operators move to Ethernet for AI back-ends

The shift is operational and economic more than it is about raw latency: one network model shared with the rest of the data center, a multi-vendor supply chain, and lower cost per port at 400G and 800G add up fast on a large build. As a third-party example, Meta has described training its largest models over a RoCE Ethernet fabric on a 24,000-GPU cluster, a scale once assumed to require InfiniBand. Broadcom has published adaptive load-balancing results on Tomahawk 4 and Tomahawk 5 that lift fabric utilization from roughly 55 percent under static hashing to 90 percent and above.

InfiniBand's remaining edge, a lower absolute latency floor, still matters for a set of tightly coupled HPC workloads. For most distributed-training and inference collectives at scale, a correctly tuned RoCEv2 fabric sits below the threshold that changes job completion time, which is why the operational and economic case now decides most new AI back-end builds.

How OcNOS-DC delivers the RoCEv2 path

OcNOS-DC provides the lossless Ethernet substrate that RoCEv2 requires. The switch supplies the loss-avoidance and congestion primitives; RoCEv2 is the transport that runs on the NIC. These are verified switch capabilities in OcNOS-DC today:

Silicon choice is open: OcNOS-DC runs on the Edgecore AIS800-64D and UfiSpace S9321-64E / S9321-64EO (the -64EO adds 400G ZR+) on Broadcom Tomahawk 5, and the Edgecore AS9736-64D on Tomahawk 4, all on-chip and shared-buffer platforms tuned for RoCEv2. One IP Infusion contract covers the software and the validated hardware, with one TAC and one SLA.