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* Initial draft for How-to POC * Zone.identifier file removed * Broken links in index.md fixed * Zone.identifier file removed * Review feedback incorporated * Title updated * New format for ROCm for AI TOC created * Folder structure changed * ROCm for AI index updated * Link to Llama recipe updated * Review feedback added * Feedback from Cindy added * Intro text from Cindy added * New flow suggested by Hongxia incorporated * Overview content from Cindy added, TOC updated, Meta data updated * Reference to HPC removed * Listing alignment updated * Overview page updated * Folder structure and link change resulted from TOC change updated * Content sequence updated * Meta data updated * Review feedback incorporated * Index file renamed * Conf file updated for OS compatibility info * update metadata (#4) update metadata fix spelling * Wordlist updated --------- Co-authored-by: Peter Park <peter.park@amd.com>
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AMD ROCm documentation
ROCm is an open-source software platform optimized to extract HPC and AI workload performance from AMD Instinct accelerators and AMD Radeon GPUs while maintaining compatibility with industry software frameworks. For more information, see What is ROCm?
ROCm supports multiple programming languages and programming interfaces such as
{doc}HIP (Heterogeneous-Compute Interface for Portability)<hip:index>, OpenCL,
and OpenMP, as explained in the Programming guide.
If you're using AMD Radeon™ PRO or Radeon GPUs in a workstation setting with a display connected, review {doc}Radeon-specific ROCm documentation<radeon:index>.
ROCm documentation is organized into the following categories:
::::{grid} 1 2 2 2 :gutter: 3 :class-container: rocm-doc-grid
:::{grid-item-card} Install :class-body: rocm-card-banner rocm-hue-2
- {doc}
ROCm on Linux <rocm-install-on-linux:reference/system-requirements> - {doc}
HIP SDK on Windows <rocm-install-on-windows:reference/system-requirements> - ROCm on Radeon GPUs
- {doc}
Deep learning frameworks </how-to/deep-learning-rocm> - {doc}
Build from source </how-to/build-rocm>:::
:::{grid-item-card} How to :class-body: rocm-card-banner rocm-hue-12
- Use ROCm for AI
- Use ROCm for HPC
- System optimization
- AMD Instinct MI300X performance validation and tuning
- System debugging
- Use advanced compiler features
- Set the number of CUs
- Troubleshoot BAR access limitation
- ROCm examples :::
:::{grid-item-card} Conceptual :class-body: rocm-card-banner rocm-hue-8
- GPU architecture overview
- Input-Output Memory Management Unit (IOMMU)
- File structure (Linux FHS)
- GPU isolation techniques
- Using CMake
- PCIe atomics in ROCm
- Inception v3 with PyTorch
- Oversubscription of hardware resources :::
:::{grid-item-card} Reference :class-body: rocm-card-banner rocm-hue-6
- ROCm libraries
- ROCm tools, compilers, and runtimes
- Accelerator and GPU hardware specifications
- Precision support
- Graph safe support
:::
::::