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50 lines
1.7 KiB
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50 lines
1.7 KiB
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.. meta::
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:description: How to use ROCm Compute Profiler's analyze mode
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:keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD,
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analysis, analyze mode
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************
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Analyze mode
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************
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ROCm Compute Profiler offers several ways to interact with the metrics it generates from
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profiling. Your level of familiarity with the profiled application, computing
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environment, and experience with ROCm Compute Profiler should inform the analysis method you
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choose.
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.. note::
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Analyze mode requires Python 3.9 or newer; its dependencies (numpy, pandas,
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dash, textual) drop support for older versions. Profile mode runs on Python
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3.8+. See the Python version support table in :doc:`/install/quickstart`.
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.. note::
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Analyze mode merges separate counter collection files (pmc_perf_*.csv or results_*.csv) into a unified pmc_perf.csv for analysis.
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.. note::
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Reading intermediate ``results_*.csv`` files produced by ``rocpd`` profiling is
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deprecated and will be removed in a future release. The analyze step will read ``.db``
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files directly.
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See the following sections to explore ROCm Compute Profiler's analysis and visualization
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options.
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* :doc:`cli`
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* :doc:`standalone-gui` (experimental feature)
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* :doc:`tui` (experimental feature)
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* :doc:`optiq` (graphical application)
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.. note::
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Analysis examples in this chapter borrow profiling results from the
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``vcopy.cpp`` workload introduced in :ref:`profile-example` in the
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previous chapter.
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Unless otherwise noted, the performance analysis is done on the
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:ref:`MI200 platform <def-soc>`.
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Learn about profiling with ROCm Compute Profiler in :doc:`../profile/mode`. For an overview of
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ROCm Compute Profiler's other modes, see :ref:`modes`.
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