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.. meta::
:description: Understand the AMD CDNA architectures and hardware blocks with ROCm Compute Profiler to analyze and optimize performance on AMD Instinct MI series GPUs.
:keywords: ROCm Compute Profiler, CDNA, Instinct, performance model, MI-series
.. _cdna-performance-model:
***********************************
AMD CDNA architecture (CDNA-CDNA4)
***********************************
ROCm Compute Profiler makes available an extensive list of metrics to better understand the
achieved application performance on AMD Instinct™ MI-series GPUs
including:
* CDNA™ architecture based GPUs: AMD Instinct MI100
* CDNA2 architecture based GPUs: AMD Instinct MI210, MI250, and MI250X
* CDNA3 architecture based GPUs: AMD Instinct MI300A, MI300X, and MI325X, and
* CDNA4 architecture based GPUs: AMD Instinct MI350X and MI355X.
.. note::
* For AMD Ryzen™ / RDNA™ APUs (e.g. gfx115x/RDNA3.5), see :doc:`RDNA3 <../rdna/rdna-performance-model>`.
* For top-level metrics details on CDNA and RDNA architecture, see :doc:`../performance-model`.
The table provides key details and support available for the different CDNA architectures:
✅: Supported
❌: Unsupported
**Architecture details**
.. table::
:widths: 30 30 30 30 30
+-----------------+-----------+---------------------------------+-------------------------------------+-------------------------+
|Architecture |CDNA |CDNA 2 |CDNA 3 |CDNA 4 |
+=================+===========+=================================+=====================================+=========================+
|Chip packaging |Single Die |Up to two graphics Compute Dies |One logical processor with dozen |Similar to CDNA3, |
| | |(GCDs) into single package. |chiplets, configurable with partition|Multi-Die chiplet, but |
| | | |modes. |with two I/O Dies (IODs) |
+-----------------+-----------+---------------------------------+-------------------------------------+-------------------------+
|Supported series |MI100 |MI210 |MI300A |MI350X |
| | +---------------------------------+-------------------------------------+-------------------------+
| | |MI250 |MI300X |MI355X |
| | +---------------------------------+-------------------------------------+-------------------------+
| | |MI250X |MI325X | |
+-----------------+-----------+---------------------------------+-------------------------------------+-------------------------+
|Spatial partition|❌ |❌ |Compute partition mode and |Compute partition mode |
|mode | | |Memory partition mode |and Memory partition mode|
+-----------------+-----------+---------------------------------+-------------------------------------+-------------------------+
**Data type support**
.. list-table::
:header-rows: 1
*
- Architecture
- FP32
- FP64
- FP16
- INT32 ADD/LOGIC/MAD
- INT8 DOT
- INT4 DOT
- FP32 GEMM
- FP64 GEMM
- FP16 GEMM
- BF16 GEMM
- INT8 GEMM
- Packed FP32
- TF32 GEMM
- FP8/BF8 GEMM
*
- CDNA
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ❌
- ❌
- ❌
- ❌
- ❌
- ❌
- ❌
*
- CDNA2
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ❌
- ❌
*
- CDNA3
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
*
- CDNA4
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ✅
- ❌
- ✅
To best use profiling data, it's important to understand the role of various
hardware blocks of AMD Instinct GPUs. Refer to the following top-level GPU architecture diagram to understand the hardware blocks of each architecture.
.. tab-set::
.. tab-item:: CDNA
.. image:: ../../data/conceptual/CDNA.png
:alt: CDNA top level architecture diagram with zoomed view of Compute unit
.. tab-item:: CDNA2
.. image:: ../../data/conceptual/CDNA2.png
:alt: CDNA2 top level architecture diagram with zoomed view of Compute unit
.. tab-item:: CDNA3
.. image:: ../../data/conceptual/CDNA3.png
:alt: CDNA3 top level architecture diagram with zoomed view of Accelerator Complex Dies (XCDs)
.. tab-item:: CDNA4
.. image:: ../../data/conceptual/CDNA4.png
:alt: CDNA4 top level architecture diagram
This section describes each hardware block on the GPUs as interacted with by a software developer to
give a deeper understanding of the metrics reported by profiling data. Refer to
:doc:`/tutorial/profiling-by-example` for more practical examples and details on how
to use ROCm Compute Profiler to optimize your code.
.. _mixxx-note:
.. note::
In this documentation, **MI2XX** refers to any of the CDNA2 architecture-based MI200 series GPUs, such as AMD
Instinct MI250X, MI250, and MI210 GPUs interchangeably in cases
where the exact product at hand is not relevant. For product details, see `AMD Instinct GPUs <https://www.amd.com/en/products/accelerators/instinct.html>`_.
For a comparison of AMD Instinct GPU specifications, refer to
:doc:`Hardware specifications <rocm:reference/gpu-arch-specs>`.
Hardware blocks
================
The AMD Instinct performance model is divided into the following blocks:
* :doc:`system-speed-of-light`
* :doc:`compute-unit`
* :doc:`l2-cache`
* :doc:`shader-engine`
* :doc:`command-processor`
* :doc:`references`