PaddlePaddle supports running jobs on several platforms including:
- `Kubernetes <http://kubernetes.io>`_ open-source system for automating deployment, scaling, and management of containerized applications from Google.
- `OpenMPI <https://www.open-mpi.org>`_ Mature high performance parallel computing framework.
- `Fabric <http://www.fabfile.org>`_ A cluster management tool. Write scripts to submit jobs or manage the cluster.
The user's cluster environment is not the same. To facilitate everyone's deployment, we provide a variety of cluster deployment methods to facilitate the submission of cluster training tasks, which will be introduced as follows:
We'll introduce cluster job management on these platforms. The examples can be found under `cluster_train_v2 <https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/scripts/cluster_train_v2>`_ .
`Kubernetes <http://kubernetes.io>`_ is a scheduling framework of Google open source container cluster, supporting a complete cluster solution for large-scale cluster production environment. The following guidelines show PaddlePaddle's support for Kubernetes:
These cluster platforms provide API or environment variables for training processes, when the job is dispatched to different nodes. Like node ID, IP or total number of nodes etc.
.. toctree::
:maxdepth: 1
k8s_cn.md
k8s_distributed_cn.md
`OpenMPI <https://www.open-mpi.org>`_ is a mature high-performance parallel computing framework, which is widely used in the field of HPC. The following guide describes how to use OpenMPI to build PaddlePaddle's cluster training task:
.. toctree::
:maxdepth: 1
fabric_en.md
openmpi_en.md
k8s_en.md
k8s_aws_en.md
openmpi_cn.md
`Fabric <http://www.fabfile.org>`_ is a convenient tool for program deployment and management. We provide a way to deploy and manage with Fabric. If you want to know more about it, please read the following guidelines:
.. toctree::
:maxdepth: 1
fabric_cn.md
We also support the deployment of PaddlePaddle on AWS. Learn more about:
.. toctree::
:maxdepth: 1
k8s_aws_cn.md
The examples can be found under `cluster_train_v2 <https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/scripts/cluster_train_v2>`_ .
