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Stanford Megatron-LM Compatibility
* Create stanford-megatron-lm-compatibility.rst * toc and wordlist * Update deep-learning-rocm.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * fixes and adding to main compat matrix * formatting fix * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update docs/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com> * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst * Update stanford-megatron-lm-compatibility.rst --------- Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com>
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@@ -194,6 +194,7 @@ Higgs
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Hyperparameters
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Huggingface
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ICD
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ICT
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ICV
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IDE
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IDEs
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@@ -368,6 +369,7 @@ RDC's
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RDMA
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RDNA
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README
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Recomputation
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RHEL
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RMW
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RNN
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@@ -55,6 +55,7 @@ compatibility and system requirements.
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:doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 2.1, 2.0, 1.13"
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:doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1"
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:doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.31
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:doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`,N/A,N/A,`85f95ae <https://github.com/stanford-futuredata/Megatron-LM/commit/85f95aef3b648075fe6f291c86714fdcbd9cd1f5>`_
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:doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`,2.4.0,2.4.0,N/A
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`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.17.3
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,,,
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:orphan:
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.. meta::
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:description: Stanford Megatron-LM compatibility
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:keywords: Stanford, Megatron-LM, compatibility
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.. version-set:: rocm_version latest
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********************************************************************************
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Stanford Megatron-LM compatibility
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********************************************************************************
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Stanford Megatron-LM is a large-scale language model training framework developed by NVIDIA `https://github.com/NVIDIA/Megatron-LM <https://github.com/NVIDIA/Megatron-LM>`_. It is
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designed to train massive transformer-based language models efficiently by model and data parallelism.
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* ROCm support for Stanford Megatron-LM is hosted in the official `https://github.com/ROCm/Stanford-Megatron-LM <https://github.com/ROCm/Stanford-Megatron-LM>`_ repository.
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* Due to independent compatibility considerations, this location differs from the `https://github.com/stanford-futuredata/Megatron-LM <https://github.com/stanford-futuredata/Megatron-LM>`_ upstream repository.
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* Use the prebuilt :ref:`Docker image <megatron-lm-docker-compat>` with ROCm, PyTorch, and Megatron-LM preinstalled.
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* See the :doc:`ROCm Stanford Megatron-LM installation guide <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>` to install and get started.
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.. note::
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Stanford Megatron-LM is supported on ROCm 6.3.0.
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Supported Devices
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================================================================================
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- **Officially Supported**: AMD Instinct MI300X
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- **Partially Supported** (functionality or performance limitations): AMD Instinct MI250X, MI210X
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Supported models and features
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================================================================================
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This section details models & features that are supported by the ROCm version on Stanford Megatron-LM.
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Models:
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* Bert
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* GPT
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* T5
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* ICT
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Features:
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* Distributed Pre-training
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* Activation Checkpointing and Recomputation
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* Distributed Optimizer
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* Mixture-of-Experts
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.. _megatron-lm-recommendations:
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Use cases and recommendations
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================================================================================
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See the `Efficient MoE training on AMD ROCm: How-to use Megablocks on AMD GPUs blog <https://rocm.blogs.amd.com/artificial-intelligence/megablocks/README.html>`_ post
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to leverage the ROCm platform for pre-training by using the Stanford Megatron-LM framework of pre-processing datasets on AMD GPUs.
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Coverage includes:
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* Single-GPU pre-training
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* Multi-GPU pre-training
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.. _megatron-lm-docker-compat:
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Docker image compatibility
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================================================================================
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.. |docker-icon| raw:: html
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<i class="fab fa-docker"></i>
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AMD validates and publishes `Stanford Megatron-LM images <https://hub.docker.com/r/rocm/megatron-lm>`_
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with ROCm and Pytorch backends on Docker Hub. The following Docker image tags and associated
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inventories represent the latest Megatron-LM version from the official Docker Hub.
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The Docker images have been validated for `ROCm 6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_.
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Click |docker-icon| to view the image on Docker Hub.
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.. list-table::
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:header-rows: 1
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:class: docker-image-compatibility
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* - Docker image
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- Stanford Megatron-LM
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- PyTorch
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- Ubuntu
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- Python
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* - .. raw:: html
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<a href="https://hub.docker.com/layers/rocm/stanford-megatron-lm/stanford-megatron-lm85f95ae_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-070556f078be10888a1421a2cb4f48c29f28b02bfeddae02588d1f7fc02a96a6"><i class="fab fa-docker fa-lg"></i></a>
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- `85f95ae <https://github.com/stanford-futuredata/Megatron-LM/commit/85f95aef3b648075fe6f291c86714fdcbd9cd1f5>`_
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- `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
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- 24.04
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- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
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@@ -17,6 +17,7 @@ features for these ROCm-enabled deep learning frameworks.
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* :doc:`PyTorch compatibility <../compatibility/ml-compatibility/pytorch-compatibility>`
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* :doc:`TensorFlow compatibility <../compatibility/ml-compatibility/tensorflow-compatibility>`
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* :doc:`JAX compatibility <../compatibility/ml-compatibility/jax-compatibility>`
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* :doc:`Stanford Megatron-LM compatibility <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
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* :doc:`DGL compatibility <../compatibility/ml-compatibility/dgl-compatibility>`
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This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
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@@ -30,6 +31,7 @@ See the installation instructions to get started.
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* :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
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* :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
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* :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
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* :doc:`Stanford Megatron-LM for ROCm <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
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* :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/dgl-install>`
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.. note::
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