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kubernetes-gpu\nInstall NVIDIA GPU Support on CoreOS based Kubernetes Cluster\n\n# Prerequisits\n* CoreOS based Kubernetes cluster with GPU nodes (e.g. AWS P2 instances)\n\n# Installation\nFirst install the nvidia driver via this daemonset\n```\nkubectl apply -f https://raw.githubusercontent.com/afritzler/kubernetes-gpu/master/k8s-nvidia-driver.yaml\n```\nWait until the init container finishes on each node and install the device plugin\n```\nkubectl apply -f https://raw.githubusercontent.com/afritzler/kubernetes-gpu/master/k8s-nvidia-deviceplugin.yaml\n\n```\n\n\n# Run\nTo run an example training on a GPU node, start first a base image with Tensorflow with GPU support \u0026 Keras\n```\nkubectl apply -f https://raw.githubusercontent.com/afritzler/deeplearning-workbench/master/manifests/dl-workbench.yaml\n```\nNow `exec` into the container and start an example Keras traing\n```\nkubectl exec -it deeplearning-workbench-8676458f5d-p4d2v -- /bin/bash\ncd /keras/example\npython imdb_cnn.py\n```\n\n# Open Issues\n- [ ] Label GPU nodes and add NodeSelector to daemonset\n\n\n# Acknowledgments \u0026 References\n* Build and install NVIDIA driver on CoreOS: https://github.com/squat/modulus\n* Nvidia Device Plugin: https://github.com/kubernetes/kubernetes/blob/master/cluster/addons/device-plugins/nvidia-gpu/daemonset.yaml","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fafritzler%2Fkubernetes-gpu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fafritzler%2Fkubernetes-gpu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fafritzler%2Fkubernetes-gpu/lists"}