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214 lines
8.4 KiB
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214 lines
8.4 KiB
ReStructuredText
.. meta::
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:description: Learn how to install hipDNN.
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:keywords: hipDNN, ROCm, install, prerequisites, Windows, Linux
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.. _prerequisites:
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*******************
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hipDNN installation
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*******************
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The hipDNN frontend API is distributed as a header-only library. It requires a development ROCm package installation.
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These development packages contain the ``-dev`` prefix.
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Dependencies
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============
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Before you begin, verify that your system is supported. For more information,
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see :ref:`ROCm Core SDK components <rocm:release-components>`.
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.. list-table::
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:widths: 3 3 5
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:header-rows: 1
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* - Dependency
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- Version
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- Description
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* - ROCm development installation
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- ROCm 7.12.0 or later
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- AMD GPU programming stack
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* - CMake
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- 3.25.2 or later
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- Build system generator
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* - Ninja (recommended)
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- 1.12.1 or later
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- Faster build system
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* - C++ Compiler
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- C++17 compatible
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- hipDNN API supports C++17
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.. _install-rocm:
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Install the ROCm Core SDK
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=========================
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hipDNN is included with the ROCm Core SDK on Linux and Windows. For the most
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complete installation on Linux, we recommend that developers use the
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``amdrocm-core-sdk`` meta package.
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For instructions, see :doc:`Install AMD ROCm <rocm:install/rocm>`. Use the
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selector panel on that page to view instructions appropriate for your system
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environment.
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.. _install-base:
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Install ROCm DNN libraries on Linux
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===================================
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Alternatively, if you want to install hipDNN as part of the ROCm
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DNN package (a subset of the ROCm Core SDK ``amdrocm-core-sdk``) without
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additional ROCm libraries and tools, install the ``amdrocm-dnn`` package.
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1. Complete the :doc:`ROCm installation prerequisites <rocm:install/rocm>` to
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install dependencies and configure GPU access permissions.
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2. Install the ROCm DNN package that matches your desired ROCm version,
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development package needs, and AMD GPU architecture. Package names use the
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following format:
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.. code-block:: shell-session
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amdrocm-dnn<-dev/-devel><rocm_version><-llvm_target>
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Where:
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* ``<-dev/-devel>`` specifies whether to install library files and
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headers. Omit this suffix to only install runtime packages.
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* ``-dev`` is used on Debian-based distributions, including Ubuntu.
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* ``-devel`` is used on RPM-based distributions, including RHEL and SLES.
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* ``<rocm_version>`` is the ROCm Core SDK version to install. Omit this
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suffix to install the latest available version.
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* ``<-llvm_target>`` (starting with ``gfx``) is used if you are installing
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for a single AMD GPU architecture. Omit this suffix to install for all
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architectures at the cost of disk space.
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For example: ``amdrocm-dnn-dev7.13-gfx950``
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Use the following command to install the latest DNN development package
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release for supported GPU architectures:
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.. tab-set::
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.. tab-item:: Debian-based distros
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.. code-block:: bash
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sudo apt install amdrocm-dnn-dev
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.. tab-item:: RHEL-based distros
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.. code-block:: bash
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sudo dnf install amdrocm-dnn-devel
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.. tab-item:: SLES
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.. code-block:: bash
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sudo zypper install amdrocm-dnn-devel
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.. _install-nightly:
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Install a nightly build
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=======================
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The `TheRock <https://github.com/ROCm/TheRock>`__ build system also publishes
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nightly builds for the ROCm Core SDK and its components, including MIOpen.
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See `Nightly release status
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<https://github.com/ROCm/TheRock#nightly-release-status>`__ for details.
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Verify hipDNN installation
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==========================
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The hipDNN library ships with executables that can be used to test the hipDNN library and plugins when the GPU hardware is available.
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These executables can be run individually or as a suite using the ``ctest`` driver program. (``ctest`` is isntalled as part of the CMake package.)
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Run hipDNN unit tests
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---------------------
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A suite of unit test executables are included with hipDNN. These test executables don't require the GPU hardware to run.
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Here's an example that demonstrates running these tests using ``ctest``:
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.. code-block:: shell-session
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$ ctest --test-dir /opt/rocm/bin/hipdnn
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Internal ctest changing into directory: /opt/rocm/bin/hipdnn
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Test project /opt/rocm/bin/hipdnn
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Start 1: hipdnn_data_sdk_tests
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1/9 Test #1: hipdnn_data_sdk_tests ................... Passed 0.26 sec
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Start 2: hipdnn_flatbuffers_sdk_tests
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2/9 Test #2: hipdnn_flatbuffers_sdk_tests ............ Passed 0.03 sec
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Start 3: hipdnn_backend_tests
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3/9 Test #3: hipdnn_backend_tests .................... Passed 5.77 sec
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Start 4: hipdnn_frontend_tests
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4/9 Test #4: hipdnn_frontend_tests ................... Passed 0.09 sec
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Start 5: hipdnn_test_sdk_tests
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5/9 Test #5: hipdnn_test_sdk_tests ................... Passed 9.71 sec
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Start 6: hipdnn_plugin_sdk_tests
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6/9 Test #6: hipdnn_plugin_sdk_tests ................. Passed 0.03 sec
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Start 7: hipdnn_public_backend_tests
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7/9 Test #7: hipdnn_public_backend_tests ............. Passed 0.25 sec
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Start 8: hipdnn_backend_logging_shutdown_tests
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8/9 Test #8: hipdnn_backend_logging_shutdown_tests ... Passed 0.20 sec
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Start 9: hipdnn_public_frontend_tests
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9/9 Test #9: hipdnn_public_frontend_tests ............ Passed 1.88 sec
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100% tests passed, 0 tests failed out of 9
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Replace ``/opt/rocm`` with your ROCm install folder when running this ``ctest`` command.
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Run hipDNN samples
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------------------
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The sample programs shipped with hipDNN require AMD GPU hardware to execute.
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The samples execute supported tensor operations on GPU hardware using the plugins installed with hipDNN.
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This example demonstrates running the entire set of samples using ``ctest``:
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.. code-block:: shell-session
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$ ctest --test-dir /opt/rocm/bin/hipdnn_samples
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Internal ctest changing into directory: /opt/rocm/bin/hipdnn_samples
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Test project /opt/rocm/bin/hipdnn_samples
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Start 1: hipdnn_sample_conv_fprop
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1/15 Test #1: hipdnn_sample_conv_fprop ............................. Passed 5.40 sec
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Start 2: hipdnn_sample_conv_dgrad
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2/15 Test #2: hipdnn_sample_conv_dgrad ............................. Passed 4.79 sec
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Start 3: hipdnn_sample_conv_wgrad
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3/15 Test #3: hipdnn_sample_conv_wgrad ............................. Passed 7.64 sec
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Start 4: hipdnn_sample_fused_conv_fprop_activ
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4/15 Test #4: hipdnn_sample_fused_conv_fprop_activ ................. Passed 5.40 sec
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Start 5: hipdnn_sample_fused_conv_fprop_bias_activ
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5/15 Test #5: hipdnn_sample_fused_conv_fprop_bias_activ ............ Passed 5.79 sec
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Start 6: hipdnn_sample_conv_fprop_deterministic
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6/15 Test #6: hipdnn_sample_conv_fprop_deterministic ............... Passed 5.10 sec
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Start 7: hipdnn_sample_bn_inference
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7/15 Test #7: hipdnn_sample_bn_inference ........................... Passed 2.98 sec
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Start 8: hipdnn_sample_bn_inference_with_variance
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8/15 Test #8: hipdnn_sample_bn_inference_with_variance ............. Passed 2.97 sec
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Start 9: hipdnn_sample_bn_training
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9/15 Test #9: hipdnn_sample_bn_training ............................ Passed 3.09 sec
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Start 10: hipdnn_sample_fused_bn_training_activ
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10/15 Test #10: hipdnn_sample_fused_bn_training_activ ................ Passed 3.48 sec
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Start 11: hipdnn_sample_bn_backward
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11/15 Test #11: hipdnn_sample_bn_backward ............................ Passed 3.31 sec
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Start 12: hipdnn_sample_fused_bn_inference_activ
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12/15 Test #12: hipdnn_sample_fused_bn_inference_activ ............... Passed 3.35 sec
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Start 13: hipdnn_sample_fused_bn_inference_drelu_bn_backward
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13/15 Test #13: hipdnn_sample_fused_bn_inference_drelu_bn_backward ... Passed 2.88 sec
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Start 14: hipdnn_sample_fused_bn_inference_variance_activ
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14/15 Test #14: hipdnn_sample_fused_bn_inference_variance_activ ...... Passed 3.34 sec
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Start 15: hipdnn_sample_serialization_roundtrip
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15/15 Test #15: hipdnn_sample_serialization_roundtrip ................ Passed 3.09 sec
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100% tests passed, 0 tests failed out of 15
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Replace ``/opt/rocm`` with your ROCm install folder when running this ``ctest`` command.
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See `hipDNN Samples <https://github.com/ROCm/rocm-libraries/blob/develop/projects/hipdnn/samples/README.md>`_ for further details on running these sample programs and their operation.
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