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In this guide, learn how to use GPUDirect RDMA with RoCE-based backend fabrics at CoreWeave, and how to test it with NCCL. GPUDirect RDMA over RoCE lets multi-Node GPU workloads move data directly between GPU memory and the network fabric, which is essential for high-throughput, low-latency collective operations in distributed training and HPC jobs. This guide targets platform engineers and ML practitioners who deploy Pods on RoCE-enabled CoreWeave clusters.

Prerequisites

CoreWeave supports GPUDirect RDMA over RoCE (RDMA over Converged Ethernet) for some GPU instance types built on Spectrum-X Ethernet fabrics. To use this feature, you must:
  • Select a Node Pool with RoCE support.
  • Install NCCL, and UCX or OFED userspace as needed, in the Pod image.
  • Configure the Pods to use GPUDirect RDMA over RoCE.
For background on CoreWeave’s high-performance fabrics, see About CoreWeave HPC interconnects.

Select a Node Pool with RoCE support

To use GPUDirect RDMA over RoCE, make sure the Node Pool has Nodes connected to a RoCE-capable fabric, as shown in the GPU instance types list and your contract. All Nodes on these clusters have the required RoCE kernel drivers and firmware pre-installed. CKS manages the RoCE driver, NIC configuration, and fabric integration. To avoid Node instability, don’t install additional low-level driver management tools inside your Pods. If you’re unsure whether a given cluster or Node Pool has RoCE enabled, contact your CoreWeave representative.

Configure the Pods

Configure the Pods to use GPUDirect RDMA over RoCE. The following sections describe the three required configuration tasks, with an optional fourth task for debug logging:
  1. Request the RoCE RDMA resource so Pods land on Nodes with RoCE.
  2. Attach RoCE interfaces into the Pod using Multus.
  3. Configure NCCL (and optionally UCX) to use those interfaces.
On some platforms (for example, SUNK NodeSets such as gb300-4x-e), the NodeSet handles steps 1 and 2. For direct Kubernetes workloads, you configure them explicitly in the Pod spec. After you complete these steps, your Pods run on RoCE-capable Nodes, have the RoCE backend interfaces attached, and use NCCL configured for GPUDirect RDMA traffic.

Request the RoCE RDMA resource

Set the value of spec.containers.resources.requests.rdma/ib to 1. This value doesn’t indicate the number of RoCE devices requested. Kubernetes uses it as a boolean to schedule Pods onto servers that expose RoCE RDMA resources. Kubernetes schedules resources through requests and limits. When you specify only limits, Kubernetes sets requests to the same amount as the limit. For more information, see the Kubernetes documentation on container resource management. For a full YAML example showing how to set the rdma/ib value in the Pod spec for both requests and limits, see Kubernetes example.

Attach RoCE interfaces with Multus

CoreWeave exposes RoCE backend interfaces into Pods using Multus CNI and NetworkAttachmentDefinition (NAD) objects. On RoCE-enabled clusters, CoreWeave defines NADs that map host RoCE devices (for example, Spectrum-X ibs#p# ports) into Pod network interfaces through MACVLAN and VRF configuration. On some clusters, CoreWeave provides a set of per-port NADs (for example, ibs0p0-macvlan and ibs0p1-macvlan). In that case, the k8s.v1.cni.cncf.io/networks annotation contains one entry per backend interface, for example:
Key points:
  • name and namespace must match the RoCE NADs configured in your cluster.
  • The attached interfaces appear inside the Pod as additional network devices (for example, net1 and net2), and NCCL and UCX use them for GPUDirect RDMA traffic.
  • Some clusters also provide a single “backend” NAD name. Your CoreWeave representative can provide the correct annotation for your cluster.

GB300 multi-rail Pod requirements

On GB300 RoCE, a direct Kubernetes Pod that needs RoCE access must include all of the following. Without the Multus annotations, only eth0 is available in the Pod and no ibp devices are exposed.
  • All 16 Multus annotations, one per backend interface, as shown in the preceding example (ibs0p0-macvlan through ibs3p3-macvlan in the cw-multus namespace).
  • The RDMA resource request rdma/ib: 1 in resources.
  • The IPC_LOCK capability:
On SUNK NodeSets such as gb300-4x-e, the NodeSet handles the Multus attachment, so you don’t add these annotations to the Slurm job yourself.

Configure NCCL and UCX for RoCE

To configure the Pod to use GPUDirect RDMA over RoCE, set these environment variables:
  • NCCL_SOCKET_IFNAME: The front-end interface name for NCCL’s TCP-based control and out-of-band communication. Commonly set to the primary Pod interface, for example eth0.
  • NCCL_IB_HCA: The RDMA interfaces that NCCL uses for GPUDirect RDMA collectives. On GB300 RoCE clusters, this is the ibp interface. On other clusters, it must match the RoCE device naming or the Pod interfaces that Multus creates (for example, a specific interface name or a comma-separated list such as net1,net2), depending on how you configured your cluster.
  • UCX_NET_DEVICES (optional, for UCX-based stacks): The network devices to use for UCX communication. Set this to the same interfaces that handle RoCE-based RDMA traffic.
  • UCX_TLS (optional, for UCX-based stacks): The UCX transports to enable. For RoCE, you might use tcp (and other transports as needed), depending on your UCX configuration and application requirements.

Environment variables that differ from InfiniBand

RoCE on CoreWeave uses an IPv6 address family and an Ethernet traffic class, so a few NCCL variables differ from the InfiniBand recipe. On RoCE clusters such as GB300, set these in addition to the preceding variables:
  • NCCL_IB_ADDR_FAMILY: Set to AF_INET6. RoCE addressing on CoreWeave is IPv6, unlike InfiniBand.
  • NCCL_IB_TC: The RoCE traffic class, for example 96 on GB300.
  • NCCL_NET_PLUGIN: Set to none for typical jobs. The Spectrum-X plugin is only relevant for large jobs at the scale of roughly 10,000 or more GPUs.
For the full side-by-side comparison of InfiniBand and RoCE variables, see NCCL configuration reference for CoreWeave fabrics. The following sections provide complete Kubernetes and Slurm examples that combine these configuration steps.

UCX and GPUDirect RDMA on GB300 RoCE

NCCL and UCX use different RDMA data paths, so a node where NCCL tests pass doesn’t guarantee that UCX-based workloads work. This matters for stacks that use UCX as their RDMA backend, including NIXL (used by vLLM for disaggregated prefill and decode) and MPI applications. NIXL can’t use NCCL as a backend, so it depends entirely on a correctly built UCX. UCX-based GPUDirect RDMA on GB300 RoCE requires rdma-core version 54 or later, with UCX built against it. A container whose UCX is built against an older rdma-core initializes successfully, including detecting nvidia-peermem and DMA-BUF, but fails during actual data transfer. CoreWeave’s nccl-tests images, published at ghcr.io/coreweave/nccl-tests, include a compatible UCX. Symptoms of an rdma-core mismatch:
  • UCX initialization succeeds, but data transfer fails with a remote operation error reporting vendor_err 0x89, or with Unexpected UCX error: Input/output error.
  • NCCL tests pass on the same nodes, because NCCL’s built-in verbs path handles GPU memory differently than UCX’s path.
Set these UCX variables for GB300 RoCE. Use the mlx5 transports, not rc_verbs or ud_verbs:
If a UCX workload that previously worked suddenly fails across multiple Pods at once with Destination is unreachable, that points to a fabric-level event rather than a container or configuration problem. Check whether other jobs on the same fabric are affected before changing your job, and see Read IB and RoCE node labels for placement to check backend link health.

Optional: Enable extended NCCL logging

To increase the verbosity of NCCL’s logging, set the NCCL_DEBUG environment variable to INFO for extra debug information. This can help diagnose issues with RDMA support, but it increases the log file size, so disable it when testing is complete. For more logging options, see NCCL_DEBUG in the NCCL documentation.

Kubernetes example

When deploying a Kubernetes Pod in the cluster, use the highlighted lines in the following example to:
  • Set the rdma/ib value in the Pod spec for both requests and limits.
  • Attach RoCE backend interfaces through the k8s.v1.cni.cncf.io/networks annotation.
  • Set the required environment variables.
Setting NCCL_DEBUG to INFO enables extended logging. Remove this variable when you don’t need extended logging.

Slurm example

When deploying a Slurm job on a cluster configured for RoCE (for example, a SUNK cluster using gb300-4x-e NodeSets), use the highlighted lines in the following example to set the required environment variables. Remove NCCL_DEBUG when you don’t need extended logging.

Test with NCCL

CoreWeave provides several sample NCCL test jobs for use with MPI Operator or Slurm. These jobs live in the nccl-tests repository, and you can use them to test GPUDirect RDMA support with RoCE. These NCCL test jobs validate NCCL, but they don’t validate UCX-based workloads such as NIXL, because UCX uses a different RDMA path. To validate UCX, use a UCX-based test such as ucx_perftest from a container with a compatible rdma-core.
Last modified on July 14, 2026