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  1. Hadoop YARN
  2. YARN-6043

[HDL] Tensorflow on YARN



    • Type: New Feature
    • Status: Open
    • Priority: Major
    • Resolution: Unresolved
    • Affects Version/s: None
    • Fix Version/s: None
    • Component/s: None
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      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.


        1. TensorFlow_on_YARN_design.pdf
          225 kB
          Zhankun Tang

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              • Assignee:
                drankye Kai Zheng
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