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TSC Voting Members


Company

Name

TSC members

ZTE

Tao Liu, Shiying Jin, Liya Yuan

China Mobile

Qi Sun

China Unicom

Tengfei Liu, Ao Li

ICT,CASYuwei Wang

TSC Meeting Info

Adlik Technical Steering Committee meetings are open to the public and held every two weeks on Tuesday from 12/03/2019. You can see Adlik TSC calender and subscribe to its mailing list adlik-tsc@lists.lfai.foundation which will send you TSC meeting information on https://lists.lfai.foundation/g/adlik-tsc

The TSC meeting agenda is published prior to the meeting. If you have a topic that you'd like to discuss, please email your requested agenda item to  adlik-tsc@lists.lfai.foundation to be added to an upcoming meeting.

Zoom Details

Topic: Adlik TSC Meeting (Bi-Weekly)
Time: 03:00 PM Beijing, Shanghai
          Every 2 weeks on Tuesday until Oct 18, 2021
Join Zoom Meeting
https://zoom.us/j/3667818723

06/02

  1. Zoom meeting:TSC_20200602.mp4
  2. Roll Call


Company

Attendee

TSC members

ZTE

Tao Liu, Shiying Jin, Liya Yuan, Chengcan Wang

China Mobile

Jie Wu

China Unicom


ICT,CAS

Yuwei Wang

Other attendees

AIIAShuo Liu
  1. Status of open action items

    1. Action/ Further study on possible solution for mapping, procedure to apply Adlik in ORAN. Propose a CR for ORAN standardization. 
      1. In progress, 3 CRs will be presented at ORAN WG2 AI/ML meeting on next Monday.
    2. Action/ @Tao Liu for documentation on interface description.
      1. Will be done along with other documentation, suggest to include all of them in a doc folder.
    3. Action/ @Liya Yuan to contact with AIIA open source group to find out the requirements and solutions.
      1. In progress, an automated benchamark test solution has been proposed.
    4. Action/ @Tao Liu to prepare for online video introdution to using Adlik.
      1. There will be 2 events where we can promote Adlik, will be recorded as online video.
  2. Work report and plans

    1. Release management:
      1. Will be released on June 15, draft PR has been sent to LF AI.
    2. Features of Model optimizer,Serving engine,Automated test can be found here: Release 0.1.0
  3. Open discussion

05/19

  1. Zoom meeting:TSC_20200519.mp4
  2. Roll Call


Company

Attendee

TSC members

ZTE

Tao Liu, Shiying Jin, Liya Yuan, Chengcan Wang

China Mobile


China Unicom

Tengfei Liu

ICT,CAS

Kang Li

Other attendees



  1. Status of open action items

    1. Action/ Further study on possible solution for mapping, procedure to apply Adlik in ORAN. Propose a CR for ORAN standardization. 
      1. Will discuss it tomorrow afternoon.
  2. Work report and plans

    1. Release management:
      1. The first release is expected to be published on June 15.
    2. Model optimizer:
      1. A new branch has been created on Github, code and documentation are both ready.
      2. Related documentation will be posted on Zhihu, and a video introduction will be delivered next month.
    3. Serving engine:
      1. Interfaces for getting the model online/offline are completed.
        1. Action/ @Tao Liu for documentation on interface description.
      2. Compiling toolchain for ARM architecture.
      3. Support for auto optimization for parameters.
      4. Test for all the supported environment.
        1. Collabration with AIIA benchmark test for Inference frameworks.
        2. Action/ @Liya Yuan to contact with AIIA open source group to find out the requirements and solutions.
      5. Colleagues from China Unicom are added as committers. 
      6. Action/ @Tao Liu to prepare for online video introdution to using Adlik.
  3. Open discussion
    1. A WeChat group is established for community communication.

04/21

  1. Zoom meeting:TSC_20200421.mp4
  2. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan, Bintao Han, Chengcan Wang

      China Mobile

      Qi Sun, Xiang Li

      China Unicom

      Tengfei Liu

      Other attendees



  3. Status of open action items

    1. Action/ Further study on possible solution for mapping, procedure to apply Adlik in ORAN.
      1. Come up with a solution on next TSC meeting.
  4. Follow up on Adlik+ORAN discussion
    1. Presentation on integrating model compiling(which can be done by Adlik) in ML workflow in ORAN- by Bingtao Han
      1. Before deployment, a model needs to go through the model optimization and compiling pipeline.
      2. Action/ Propose a CR for ORAN standardization. 
    2. Discussion on ORAN previous proposal for model deployment  - by Qi Sun
      1. Three possible solutions, mapping to the cloud, edge and device solutions of Adlik.
    3. Use case for release C need to be further discussed.
  5. Work report and plans

    1. Model optimizer:
      1. Coding and testing for quantilization and pruning are almost done, document in progress. Code will be pushed to github in two weeks. Will implement more algorithms afterwards.
    2. Serving engine: Performance test for TF lite and tensorflow 2.1 runtime.
      1. In progress: 1) Compiler for lite; 2) Some new features, e.g. interfaces for model onboarding.
      2. Plan to test Adlik on ARM.
  6. Open discussion

04/08

  1. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan, Bintao Han, Wei Meng

      China Mobile

      Qi Sun, Xiang Li

      China Unicom

      Tengfei Liu, Ao Li

      Other attendees



  2. Status of open action items

  3. Invited presentation from ORAN - Qi Sun
    1. Introduced projects in ORAN B release https://wiki.o-ran-sc.org/pages/viewpage.action?pageId=1179662.
    2. Introduced ML flow involved in traffic steering use case.
  4. Introduction to Adlik and possible solution of integration in ORAN open source
    1. Adlik can be used to optimize ML models before deploying to RIC platform.
  5. Work report and plans

    1. 2 features were merged in master: Support for TF lite runtime and ML runtime.
    2. Updated data of ResNet50 benchmark test.
  6. Open discussion
    1. To deploy ML/DL models in RIC platform, the following need to be taken into consideration:
      1. Platform expansion to support resource allocation
      2. Generic xAPP that supports interaction with other xAPP
    2. Will further discuss about proposing a new use case in ORAN Release C. A demo for the use case is expected to be delivered based on ORAN release B.
    3. Action/ Further study on possible solution for mapping, procedure to apply Adlik in ORAN.


03/24

  1. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan

      China Mobile


      China Unicom

      Ao Li, Tengfei Liu

      Other attendees



  2. Status of open action items

    1. ActionGitHub documentation for releases.
  3. Follow up on Adlik+MEC discussion

    1. The pull request of Benchmark code is on Github.

  4. Work report and plans

    1. Benchmark test.
    2. New runtime supporting ML algorithms.
    3. Pruning is 80% finished, will be pushed to Optimizer repo. 
  5. Open discussion
    1. Questions from Tengfei Liu:
      1. Difference between Adlik and other inference framework
        1. Adlik is product driven and focus more on quick deployment of models in production environment, which enables heterogeneous computing better model scheduling, less resource consumption.
      2.  What can we do?
        1. Provide your requirements derived from your practices in concrete cases.
        2. Use it in your projects and do techinical verification.


03/10

  1. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Shiying Jin, Liya Yuan

      China Mobile


      China Unicom

      Ao Li, Tengfei Liu

      Other attendees



  2. Status of open action items

    1. ActionArticle about heterogeneous computing in deep learning inference

      1. Published at https://www.infoq.cn/article/eg4KWZd1UoFwjSsUzfgt
    2. Action/ GitHub documentation for releases

      1. Will be updated soon.
  3. Follow up on Adlik+MEC discussion

    1. Benchmark code in progress.

    2. Ao Li from China Unicom presented benchmark-test China Unicom.pptx, discussed possible scenarios, testing metrics and use cases.
  4. Work report and plans

    1. developing features about support for tensorflow lite runtime, support for ML models.

02/25

  1. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan

      China Mobile


      China Unicom

      Tengfei Liu, Ao Li

      Other attendees



  2. Status of open action items

    1. ActionUsability and inference performance related issues to be created on Github.

      1. Benchmark feature has been created as an issue.

    2. Action/ Article about heterogeneous computing in deep learning inference

      1. A draft version will be delivered before this weekend.

    3. Action/ GitHub documentation for releases

      1. Under discussion.

    4. Action/ Enable DCO on Github

  3. Follow up on Adlik+MEC discussion

    1. Benchmark Test presented by Tao Liu benchmarkTest-cn.pptx,about the procedure, metrics, environment of the performance test. Code to be expected on github by next TSC meeting.

    2. Models like MobileNet, Inception V3 can be added as new test models. 

    3. Metrics like latency can be added as new metrics.

  4. Work report and plans

    1. Shiying Jin: planning support for machine learning models, enhanced interface for inference, etc.

02/11

  1. Roll Call
    1. ZTE: Tao Liu, Shiying Jin, Liya Yuan
  2. Status of open action items

    1. Action/ Further discussion on ingration of Adlik in MEC. ----- Discussion materials will be provided and discussed via emails first.

    2. ActionDocumentation for detailed information about how to use the compiler. ----- Will be included as a new feature.

  3. Work report and plans
    1. Taoliu: Discussed with China Unicom and concluded some directions to work on: a. usability(ease the use of Adlik  and provide automated optimzation of parameters); b. inference performance( testbed, standard testing including model, framework and metrics). Corresponding issues will be created on Github.
    2. Shiying Jin: planning RSE(Realtime smart engine) that supports the management of machine learning models. 
    3. Liya Yuan: Since several meetups and outreach activities are yet to come, detailed document need to be prepared in advance.

12/17

  1. Roll Call


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan

      China Mobile

      Qi Sun

      China Unicom

      Tengfei Liu

      Other attendees



  2. Adlik TSC chair election

    1. TSC voted and approved Liya Yuan as Adlik TSC chair.

  3. Status of open action items

    1. Further discussion on ingration of Adlik in MEC. ----- Discussion materials will be provided and discussed via emails first.

    2. Documentation for detailed information about how to use the compiler. ----- Will be included as a new feature.

  4. Work report and plans

    1. Roadmap is updated on Github.

    2. FPGA compiler and runtime will be developed first.

  5. Open Discussion

    1. Call for more developers to contribute to Adlik, e.g. to enable support for more op.

12/03

  1. Self introdution of TSC members and developers


    1. Company

      Attendee

      TSC members

      ZTE

      Tao Liu, Shiying Jin, Liya Yuan

      China Mobile

      Qi Sun

      China Unicom

      Tengfei Liu, Ao Li

      Other attendees


      Vishnu Ram

  2. Adlik code walkthrough

    1. Introduction to the two sub projects, model compiler and model serving(Tao Liu and Shiying Jin).

      1.  Q: How to give input to the model compiler? A: It's shown in the simpleMNIST demo.

      2.  Q: I have to always use the name mnist.h5 and manually input the layers in this compile_model.py? A: Further documentation will show how to get these parameters and pass them to compiler.

  3.  Adlik work plans

    1.  New features in progress: support for ARM CPU and FPGA; support for quantilization(Tao Liu).

  4. Open Discussion

    1. Adlik intergration with MEC(Ao Li)

      1. The interface requirements need further discussion.

      2. Requirements for APIs can be written collaboratively with ITU-T FG ML5G.

  5. Actions

    1. Further discussion on ingration of Adlik in MEC.

    2. Documentation for detailed information about how to use the compiler.

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