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reorganize pages add a new ROCM support page
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.. _rocm-support: | ||
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################## | ||
AMD ROCm Support | ||
################## | ||
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.. contents:: Table of Contents | ||
:local: | ||
:depth: 2 | ||
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********** | ||
Overview | ||
********** | ||
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.. note:: | ||
ROCm support in Determined is experimental. Features and configurations may change in future releases. We recommend testing thoroughly in a non-production environment before deploying to production. | ||
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Determined provides experimental support for AMD ROCm GPUs in Kubernetes deployments. Determined | ||
provides prebuilt Docker images for ROCm, including the latest ROCm 6.1 version with DeepSpeed | ||
support for MI300x users: | ||
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- `pytorch-infinityhub-dev | ||
<https://hub.docker.com/repository/docker/determinedai/pytorch-infinityhub-dev/tags>`__ | ||
- `pytorch-infinityhub-hpc-dev | ||
<https://hub.docker.com/repository/docker/determinedai/pytorch-infinityhub-hpc-dev/tags>`__ | ||
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You can build these images locally based on the Dockerfiles found in the `environments repository | ||
<https://github.com/determined-ai/environments/blob/main/Dockerfile-infinityhub-pytorch>`__. | ||
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For more detailed information about configuration, visit the :ref:`helm-config-reference` or visit | ||
:ref:`rocm-known-issues` for details on current limitations and troubleshooting. | ||
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.. _rocm-config-k8s: | ||
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************************************** | ||
Configuring Kubernetes for ROCm GPUs | ||
************************************** | ||
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To use ROCm GPUs in your Kubernetes deployment: | ||
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1. Ensure your Kubernetes cluster has nodes with ROCm-capable GPUs and the necessary drivers installed. | ||
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2. In your Helm chart values or Determined configuration, set the following: | ||
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.. code-block:: yaml | ||
resourceManager: | ||
defaultComputeResourcePool: rocm-pool | ||
resourcePools: | ||
- pool_name: rocm-pool | ||
gpu_type: rocm | ||
max_slots: <number_of_rocm_gpus> | ||
3. When submitting experiments or launching tasks, specify ``slot_type: rocm`` in your experiment configuration. | ||
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********************************* | ||
Using ROCm Images in Experiments | ||
********************************* | ||
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To use ROCm images in your experiments, specify the image in your experiment configuration: | ||
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.. code-block:: yaml | ||
environment: | ||
image: determinedai/pytorch-infinityhub-dev:rocm6.1-pytorch2.1-deepspeed0.10.0 | ||
Ensure that your experiment configuration also specifies ``slot_type: rocm`` to use ROCm GPUs. | ||
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.. _rocm-known-issues: | ||
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****************************** | ||
Known Issues and Limitations | ||
****************************** | ||
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- **Agent Deprecation**: Agent-based deployments are deprecated for ROCm support. Use Kubernetes with ROCm support for your deployments. | ||
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- **HIP GPU Errors**: Launching experiments with ``slot_type: rocm`` may fail with the error | ||
``RuntimeError: No HIP GPUs are available``. Ensure compute nodes have compatible ROCm drivers and | ||
libraries installed and available in default locations or added to the ``PATH`` and/or ``LD_LIBRARY_PATH``. | ||
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- **Boost Filesystem Errors**: You may encounter the error ``boost::filesystem::remove: Directory | ||
not empty`` during ROCm operations. A workaround is to disable per-container ``/tmp`` using bind mounts | ||
in your experiment configuration or globally using the ``task_container_defaults`` section in your master configuration: | ||
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.. code:: yaml | ||
bind_mounts: | ||
- host_path: /tmp | ||
container_path: /tmp |
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