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Posted to yarn-dev@hadoop.apache.org by "Kai Zheng (JIRA)" <ji...@apache.org> on 2016/12/30 01:41:58 UTC

[jira] [Created] (YARN-6043) [HDL] Tensorflow on YARN

Kai Zheng created YARN-6043:
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             Summary: [HDL] Tensorflow on YARN
                 Key: YARN-6043
                 URL: https://issues.apache.org/jira/browse/YARN-6043
             Project: Hadoop YARN
          Issue Type: New Feature
            Reporter: Kai Zheng


As discussed in the umbrella HADOOP-13944, we'd like to work and support Deep Learning on Hadoop. As a beginning, we implemented a prototype running Tensorflow on YARN. Preliminarily the work provides a tool yarn-tf allowing users to submit and run a Tensorflow job (say mnist.py) in a YARN cluster. It allocates and launches a Tensorflow cluster in YARN dynamically, executing the job, and then destroys the cluster after the work is done. It doesn't require Python and Tensorflow binary installations be done previously on YARN nodes (on client host, Python is required if the job is written in Python). It doesn't go in the Docker approach. Given an existing Hadoop cluster, it's pretty easy to run a Tensorflow job using the provided yarn-tf.jar bundle (the TF core library and our JNI wrapper) and yarn-tf tool.

In this jira we'll post our design documenting how we did it and the general approach. The prototype work is under polishing and will be public here soon.

Filing this as unassigned as it's a team work. Your thoughts and feedback are welcome.



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