ROCm Containers Collection
Link to section 'What is ROCm Containers?' of 'ROCm Containers Collection' What is ROCm Containers?
The AMD Infinity Hub contains a collection of advanced AMD GPU software containers and deployment guides for HPC, AI & Machine Learning applications, enabling researchers to speed up their time to science. Containerized applications run quickly and reliably in the high performance computing environment with full support of AMD GPUs. A collection of Infinity Hub tools were deployed to extend cluster capabilities and to enable powerful software and deliver the fastest results. By utilizing Singularity and Infinity Hub ROCm-enabled containers, users can focus on building lean models, producing optimal solutions and gathering faster insights. For more information, please visit AMD Infinity Hub.
Users can download ROCm containers from the AMD Infinity Hub and run them directly using Singularity instructions from the corresponding container’s catalog page.
In addition, a subset of pre-downloaded ROCm containers wrapped into convenient software modules are provided. These modules wrap underlying complexity and provide the same commands that are expected from non-containerized versions of each application.
On Bell, type the command below to see the lists of ROCm containers we deployed.
module load rocmcontainers module avail ------------ ROCm-based application container modules for AMD GPUs ------------- cp2k/20210311--h87ec1599 deepspeed/rocm4.2_ubuntu18.04_py3.6_pytorch_1.8.1 gromacs/2020.3 (D) namd/2.15a2 openmm/7.4.2 pytorch/1.8.1-rocm4.2-ubuntu18.04-py3.6 pytorch/1.9.0-rocm4.2-ubuntu18.04-py3.6 (D) specfem3d/20201122--h9c0626d1 specfem3d_globe/20210322--h1ee10977 tensorflow/2.5-rocm4.2-dev [....]
Some of these modules use the container build-in MPI libraries (you may get some error messages like "Cannot load module because these module(s) are loaded: openmpi") and may require
module unload openmpi.
Link to section 'Examples of running ROCm-based containers on AMD GPUs' of 'ROCm Containers Collection' Examples of running ROCm-based containers on AMD GPUs
Examples below show how to run some containerized applications using rocmcontainers modules. In all cases, the general workflow follows the same pattern (load the rocmcontainers module; load specific application's module; run the application as if it was built natively). Additional information can be found in module help output and on each application's AMD Infinity Hub page.