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Setonix can support Machine Learning workloads with the use of the large number of AMD GPUs installed on the system. AMD maintains a TensorFlow branch with added support for its GPUs. An official AMD container is also available but, unfortunately, it unusable on Setonix due to its lack of support for both , the Cray MPI and some core Python packages. Nevertheless, Pawsey has developed its own TensorFlow container, which can properly run on Setonix. This container is installed on Setonix and available through the module system. The Pawsey TensorFlow container is the only supported way to run TensorFlow on Setonix.
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FROM quay.io/pawsey/tensorflow:2.12.1.570-rocm5.6.0
To pull the image to your local desktop with Docker you can use:
$ docker pull quay.io/pawsey/tensorflow:2.12.1.570-rocm5.6.0
To know more about our recommendations of container builds with Docker and later translation into Singularity format for their use in Setonix please refer to the Containers Documentation.
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