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ROCm/docs/how-to/gpu-performance/mi300x.rst
anisha-amd a98236a4e3 Main Docs: references of accelerator removal and change to GPU (#5495)
* Docs: references of accelerator removal and change to GPU

Co-authored-by: Leo Paoletti <164940351+lpaoletti@users.noreply.github.com>
Co-authored-by: Pratik Basyal <pratik.basyal@amd.com>
2025-10-16 11:22:10 -04:00

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.. meta::
:description: How to configure MI300X GPUs to fully leverage their capabilities and achieve optimal performance.
:keywords: ROCm, AI, machine learning, MI300X, LLM, usage, tutorial, optimization, tuning
**************************************
AMD Instinct MI300X performance guides
**************************************
The following performance guides provide essential guidance on the necessary
steps to properly `configure your system for AMD Instinct™ MI300X GPUs
<https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
They include detailed instructions on system settings and application
:doc:`workload tuning </how-to/rocm-for-ai/inference-optimization/workload>` to
help you leverage the maximum capabilities of these GPUs and achieve
superior performance.
* `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`__
covers essential system settings and system management practices to configure
your AMD Instinct MI300X system for performance.
* :doc:`/how-to/rocm-for-ai/inference-optimization/workload` covers steps to
optimize the performance of AMD Instinct MI300X Series GPUs for HPC
and deep learning operations.
* :doc:`/how-to/rocm-for-ai/inference/benchmark-docker/vllm` introduces a preconfigured
environment for LLM inference, designed to help you test performance with
popular models on AMD Instinct MI300X Series GPUs.