3.9 KiB
AMD ROCm™ documentation
Welcome to the ROCm docs home page! If you're new to ROCm, you can review the following resources to learn more about our products and what we support:
Our documentation is organized into the following categories:
::::{grid} 1 2 2 2 :class-container: rocm-doc-grid
:::{grid-item-card} :padding: 2 Installation
Installation guides ^^^
- Linux
- {doc}
Quick-start (Linux)<rocm-install-on-linux:tutorial/quick-start> - {doc}
Linux install guide<rocm-install-on-linux:how-to/native-install/index> - {doc}
Package manager integration<rocm-install-on-linux:how-to/native-install/package-manager-integration>
- {doc}
- Windows
- {doc}
Windows install guide<rocm-install-on-windows:how-to/install> - {doc}
Application deployment guidelines<rocm-install-on-windows:conceptual/deployment-guidelines>
- {doc}
- {doc}
Install Docker containers<rocm-install-on-linux:how-to/docker> - {doc}
PyTorch for ROCm<rocm-install-on-linux:how-to/3rd-party/pytorch-install> - {doc}
TensorFlow for ROCm<rocm-install-on-linux:how-to/3rd-party/tensorflow-install> - {doc}
MAGMA for ROCm<rocm-install-on-linux:how-to/3rd-party/magma-install> - {doc}
ROCm & Spack<rocm-install-on-linux:how-to/spack>
:::
:::{grid-item-card} :padding: 2 Compatibility & support
ROCm compatibility information ^^^
- Linux (GPU & OS)
- Windows (GPU & OS)
- {doc}
Third-party<rocm-install-on-linux:reference/3rd-party-support-matrix> - {doc}
User/kernel space<rocm-install-on-linux:reference/user-kernel-space-compat-matrix> - {doc}
Docker<rocm-install-on-linux:reference/docker-image-support-matrix> - OpenMP
:::
:::{grid-item-card} :padding: 2 How-to
Task-oriented walkthroughs ^^^
- System tuning for various architectures
- Setting up for deep learning with ROCm
- GPU-enabled MPI
- System level debugging
- GitHub examples
:::
:::{grid-item-card} :padding: 2 Reference
Collated information ^^^
:::
:::{grid-item-card} :padding: 2 Conceptual
Topic overviews & background information ^^^
- GPU architecture
- GPU memory
- Compiler disambiguation
- File structure (Linux FHS)
- GPU isolation techniques
- LLVN ASan
- Using CMake
- ROCm & PCIe atomics
- Inception v3 with PyTorch
- Inference optimization with MIGraphX
- OpenMP support in ROCm
:::
::::
We welcome collaboration! If you'd like to contribute to our documentation, you can find instructions on our Contribute to ROCm docs page. Known issues are listed on GitHub.
Licensing information for all ROCm components is listed on our Licensing page.