{"repo":"kubeflow/mpi-operator","free":true,"listed":false,"github":"https://github.com/kubeflow/mpi-operator","clone":"git clone https://github.com/kubeflow/mpi-operator.git","description":"Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)","language":"Go","stars":531,"topics":["mpi","horovod","kubeflow","tensorflow","pytorch","apache-mxnet","distributed-computing","kubernetes"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"MPI Operator The MPI Operator makes it easy to run allreduce-style distributed training on Kubernetes. Please check out this blog post for an introduction to MPI Operator and its industry adoption. Installation You can deploy the operator with default settings by running the following commands: - Latest Development Version - Release Version Alternatively, follow the getting started guide to deploy Kubeflow. An alpha version of MPI support was introduced with Kubeflow 0.2.0. You must be using a version of Kubeflow newer than 0.2.0. You can check whether the MPI Job custom resource is installed via: The output should include mpijobs.kubeflow.org like the following: If it is not included, you can add it as follows using kustomize: Note that since Kubernetes v1.14, kustomize became a subcommand in kubectl . Since Kubernetes v1.21, you can also use: Creating an MPI Job You can create an MPI job by defining an MPIJob config file. See TensorFlow benchmark example config file for launching a multi-node TensorFlow benchmark training job. You may change the config file based on your requirements. Deploy the MPIJob resource to start training: Monitoring an MPI Job Once the MPIJob resource is created, you should now be able to see the created pods matching the specified number of GPUs. You can also monitor the job status from the status section. Here is sample output when the job is successfully completed. Training should run for 100 steps and takes a few minutes on a GPU cluster. You ca","default_branch":null,"files":null,"tree":[],"storefront":"/r/kubeflow","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/kubeflow/mpi-operator/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}