hadoop/hadoop-submarine/hadoop-submarine-core
Sunil G de01422c2e SUBMARINE-56. Update documentation to describe single-node PyTorch integration. Contributed by Szilard Nemeth. 2019-05-15 21:26:48 -07:00
..
src SUBMARINE-56. Update documentation to describe single-node PyTorch integration. Contributed by Szilard Nemeth. 2019-05-15 21:26:48 -07:00
README.md SUBMARINE-1. Move code base of submarine from yarn-applications to top directory. Contributed by Wangda Tan. 2019-02-17 20:03:56 +05:30
pom.xml SUBMARINE-47. Provide an implementation to parse configuration values from a YAML file for submarine run CLI. Contributed by Szilard Nemeth. 2019-04-06 07:39:13 +05:30

README.md

Overview

              _                              _
             | |                            (_)
  ___  _   _ | |__   _ __ ___    __ _  _ __  _  _ __    ___
 / __|| | | || '_ \ | '_ ` _ \  / _` || '__|| || '_ \  / _ \
 \__ \| |_| || |_) || | | | | || (_| || |   | || | | ||  __/
 |___/ \__,_||_.__/ |_| |_| |_| \__,_||_|   |_||_| |_| \___|

                             ?
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~|^"~~~~~~~~~~~~~~~~~~~~~~~~~o~~~~~~~~~~~
        o                   |                  o      __o
         o                  |                 o     |X__>
       ___o                 |                __o
     (X___>--             __|__            |X__>     o
                         |     \                   __o
                         |      \                |X__>
  _______________________|_______\________________
 <                                                \____________   _
  \                                                            \ (_)
   \    O       O       O                                       >=)
    \__________________________________________________________/ (_)

Submarine is a project which allows infra engineer / data scientist to run unmodified Tensorflow programs on YARN.

Goals of Submarine:

  • It allows jobs easy access data/models in HDFS and other storages.
  • Can launch services to serve Tensorflow/MXNet models.
  • Support run distributed Tensorflow jobs with simple configs.
  • Support run user-specified Docker images.
  • Support specify GPU and other resources.
  • Support launch tensorboard for training jobs if user specified.
  • Support customized DNS name for roles (like tensorboard.$user.$domain:6006)

Please jump to QuickStart guide to quickly understand how to use this framework.

Please jump to Examples to try other examples like running Distributed Tensorflow Training for CIFAR 10.

If you're a developer, please find Developer guide for more details.