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Elastic Deep Learning (EDL) Proposal

a. name of project or proposed name of project (must be unique within Deep Learning):

EDL

b. requested project maturity level (Graudation or Incubation stage):

Incubation stage

c. project description (what it does, why it is valuable, origin and history):

EDL is an Elastic Deep Learning framework designed to help Deep Learning Cloud Service providers to build cluster cloud services using different deep learning frameworks PaddlePaddle, Tensorflow, etc.). EDL includes a Kubernetes controller, PaddlePaddle auto-scaler, which changes the number of processes of distributed jobs to the idle hardware resource in the cluster, and a new fault-tolerable architecture.

d. statement on alignment with Deep Learning’s mission:

EDL falls within the mission of Deep Learning. The project helps cloud service providers build cluster cloud services using various deep learning frameworks.

e. Project’s license: Apache-2.0

f. Source control (GitHub, etc.): https://github.com/paddlepaddle/edl

g. External dependencies (including licenses of those dependencies):

  • Kubernetes (Apache-2.0)

  • Go                      

h. Initial committers (how long working on project):

  • Wangyi: Half a year, project founder

  • Wuyi: Half a year, main contributor

i. RACI if applicable / exists: Not applicable

j. Infrastructure requests (CI / cluster requirements): None

k. Mailing lists currently in use: None 

l. Issue tracker (GitHub by default): GitHub issue tracker

n. Release methodology and mechanics: Released on GitHub

o. Social media accounts: None

p. Existing sponsorship, if any: Baidu

q. Tool chain: It depends Kubernetes and Go.