Pratik Basyal
ed05c00103
* Formatting issue in code block and TOC fixed * Performance model reverted
48 라인
1.8 KiB
ReStructuredText
48 라인
1.8 KiB
ReStructuredText
.. meta::
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:description: ROCm Compute Profiler performance model
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:keywords: Omniperf, ROCm Compute Profiler, ROCm, performance, model, profiler, tool, Instinct,
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accelerator, AMD
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*****************
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Performance model
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*****************
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ROCm Compute Profiler makes available an extensive list of metrics to better understand
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achieved application performance on AMD Instinct™ MI-series accelerators
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including Graphics Core Next™ (GCN) GPUs like the AMD Instinct MI50, CDNA™
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accelerators like the MI100, and CDNA2 accelerators such as the MI250X, MI250,
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and MI210.
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To best use profiling data, it's important to understand the role of various
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hardware blocks of AMD Instinct accelerators. This section describes each
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hardware block on the accelerator as interacted with by a software developer to
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give a deeper understanding of the metrics reported by profiling data. Refer to
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:doc:`/tutorial/profiling-by-example` for more practical examples and details on how
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to use ROCm Compute Profiler to optimize your code.
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.. _mixxx-note:
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.. note::
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In this chapter, **MI2XX** refers to any of the CDNA2 architecture-based AMD
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Instinct MI250X, MI250, and MI210 accelerators interchangeably in cases
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where the exact product at hand is not relevant.
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For a comparison of AMD Instinct accelerator specifications, refer to
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:doc:`Hardware specifications <rocm:reference/gpu-arch-specs>`. For product
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details, see the :prod-page:`MI250X <mi200/mi250x>`,
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:prod-page:`MI250 <mi200/mi250>`, and :prod-page:`MI210 <mi200/mi210>`
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product pages.
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In this chapter, the AMD Instinct performance model used by ROCm Compute Profiler is divided into a handful of
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key hardware blocks, each detailed in the following sections:
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* :doc:`compute-unit`
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* :doc:`l2-cache`
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* :doc:`shader-engine`
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* :doc:`command-processor`
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* :doc:`system-speed-of-light` |