Warp on ROCm installation

Warp on ROCm installation#

2026-11-05

2 min read time

Applies to Linux

System requirements#

To use Warp 1.13.0, you need the following prerequisites:

  • ROCm version: 7.2.0 (MI325X), 10.1.0 (MI350X, MI355X)

  • Operating system: Ubuntu 24.04

  • GPU platform: AMD Instinct™ MI325X, MI350X, MI355X

  • PyTorch: 2.9.1 (MI325X), 2.14.0 (MI350X, MI355X)

  • Python: 3.12

Install Warp#

To run Warp with ROCm enabled, build from source using the provided Dockerfile.

Build Warp from source#

  1. Clone the Warp repository containing the Dockerfile:

    git clone -b release/1.13.0.amd0 https://github.com/AMD-Ecosystem/warp.git
cd warp

  2. Build the Docker image for your GPU architecture:

    docker build --network=host -f docker/rocm/Dockerfile --target warp_gfx942 -t warp:rocm_7.2_ubuntu24.04_py3.12_torch2.9.1 .

    docker build --network=host -f docker/rocm/Dockerfile --target warp_gfx950 -t warp:rocm10.1.0_ubuntu24.04_py3.12_torch2.14.0 .

    This builds an image with Warp 1.13.0+rocm.0 and the required dependencies, including PyTorch 2.9.1 (MI325X) or PyTorch 2.14.0 (MI350X, MI355X).

  3. Run the Docker container:

    docker run -it --rm \
   --name my_warp \
   --device /dev/kfd \
   --device /dev/dri \
   --privileged \
   --network=host \
   --group-add video \
   --cap-add=SYS_PTRACE \
   --security-opt seccomp=unconfined \
   --ipc=host \
   --shm-size=16g \
   warp:rocm_7.2_ubuntu24.04_py3.12_torch2.9.1

    docker run -it --rm \
   --name my_warp \
   --device /dev/kfd \
   --device /dev/dri \
   --privileged \
   --network=host \
   --group-add video \
   --cap-add=SYS_PTRACE \
   --security-opt seccomp=unconfined \
   --ipc=host \
   --shm-size=16g \
   warp:rocm10.1.0_ubuntu24.04_py3.12_torch2.14.0

    Note

    To check which architecture your GPUs use, run rocm_agent_enumerator | sort -u. gfx942 corresponds to MI325X, and gfx950 corresponds to MI350X and MI355X.

Test the Warp installation#

After starting the container, verify that Warp and ROCm are working correctly.

  1. Confirm that Warp is installed and detects your GPUs:

    python -c "import warp as wp; wp.init(); print(wp.get_device('cuda:0').arch_str)"

    Expected output on an AMD Instinct MI355X:

    Warp 1.13.0+rocm.0 initialized:
   ...
   Devices:
     "cpu"      : "x86_64"
     "cuda:0"   : "AMD Instinct MI355X" (288 GiB, MI350X/MI355X:sramecc+:xnack-, mempool enabled)
     ...
MI350X/MI355X:sramecc+:xnack-

    On ROCm, Warp reports AMD GPUs through the cuda:N device names.

  2. Optionally, run the Warp unit tests:

    python -m warp.tests -j 8

    Running the full test suite takes a while. Use -j to set the number of parallel test processes.

If all checks pass, proceed to run a Warp example.

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