Event planning and general information template below - To be updated by Event/Meeting Lead
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Event/Meeting Details
LF AI & Data Participation Overview:
LF AI & Data Foundation is pleased to welcome you at the LF AI & Data Day* – ONNX Community Virtual Meetup – March 2021. This event will be hosted online via Zoom video conferencing on Wednesday, March 24. The event will feature the LF AI & Data hosted Graduated Project, ONNX.
The event will cover ONNX Community updates, partner/end-user stories, and SIG/WG updates. Check back for a full agenda soon.
If you are using ONNX in your services and applications, building software or hardware that supports ONNX, or contributing to ONNX, you should attend! This is a great opportunity to meet with and hear from people working with ONNX across many companies.
Note: In order to ensure the safety of our event participants and staff due to the Novel Coronavirus situation (COVID-19) the ONNX Steering Committee decided to make this a virtual-only event via Zoom.
*LF AI & Data Day is a regional, one-day event hosted and organized by local members with support from LF AI & Data and its Projects. Learn more about the LF AI & Data Foundation here.
Event Location & Date(s):
Zoom meeting on Wednesday, March 24, 2021
Event Time:
5:00 PM - 8:00 PM - PDT (Pacific Daylight Time)
LF AI & Data Day - ONNX Online Virtual Meetup - March 24, 2021
Event Website: TBDEvent Registration: TBD https://events.linuxfoundation.org/lf-ai-data-day-onnx-community-virtual-meetup-spring/
Event Registration: https://www.cvent.com/d/37qh6p/4W?ct=50221cf5-5496-4c34-9ec0-3b52b1bf1204&_ga=2.191814634.1770376097.1607959940-1411187557.1597333659
Event Agenda/Schedule: https://events.linuxfoundation.org/lf-ai-data-day-onnx-community-virtual-meetup-spring/program/schedule/
Recording on ONNX Playlist of LF AI & Data YouTube: https://www.youtube.com/channel/UCfasaeqXJBCAJMNO9HcHfbA/playlists
Please submit any questions about LF AI & Data participation at this event to: outreach-committee@lists.lfaidata.foundation
Event Host Lead Name & Contact Details: TBDTi Zhou (Baidu) <zhouti@baidu.com>
Planning To-Do List
Tracking for to-do items, due dates, owners, and notes
To Do | Due Date | Completed | Owner | Notes |
Post presentations and recordings | March 25 | Event Lead | ||
Communicate availability of the event's recordings and presentations | March 31 | LF AI & Data | -LF AI social scheduled for TBD. |
Schedule &
Presentations - to be updatedPresentations
Time | Duration | Topic / Speaker | Deck / Recording Links |
---|---|---|---|
Wed March 24 Thur March 25 | 25m | Event Kickoff | Q&A - #onnx-general slack channel full event recording |
5 | Welcome and opening Speaker: Ti Zhou (Baidu) | ||
20 | ONNX Progress Update | ||
5:25pm PT USA 8:25am China | 100m | Community Presentations | deck / prerecording (English) optional: deck/record(Chinese) |
10m | popART: Support ONNX on IPU | ||
10m | Spring Project:Multi Backend Neural Network Auto Quantization and Deployment over ONNX | ||
10m | ONNX Runtime for Mobile Scenarios: From model to on-device inferencing | ||
10m | ONNX on PaddlePaddle 2.0: Broader Deployment and Richer Ecosystem | ||
10m | ONNX on microcontrollers | ||
10m | Monitoring and Explaining ONNX Models in Production | deck / recording | |
10m | ONNX client for Acumos Speaker: Philippe Dooze (Orange-France) (picture) | ||
10m | Deploy ONNX model seamlessly across the cloud, edge, and mobile devices using MindSpore | ||
10m | ONNX Runtime Training |
Presentation (Link)
FINAL Recordings - to be updated
Session
10m | Quantization support for ONNX using Intel Neural Compressor (formerly named Intel Low Precision Optimization Tool) Speakers: Haihao Shen (Intel - China) and Saurabh Tangri (Intel) | ||
7:05pm PT USA 10:05am China | 10m | Break | Q&A - #onnx-general slack channel |
7:15pm PT USA 10:15am China | 45m | SIG's and WG's Updates and Discussions | deck / prerecording (English) optional:deck/record (Chinese) |
10 | Architecture/Infrastructure SIG Update Chair: Ashwini Khade (Microsoft) and Jacky Chen (Microsoft) | ||
10 | Operators SIG Update Co-Chairs: Michał Karzyński (Intel) and G. Ramalingam (Microsoft) | ||
10 | Converters SIG Update | ||
10 | Model Zoo/Tutorials SIG Update | ||
5 | Q&A / Open Discussions | Q&A - #onnx-general slack channel | |
8:00pm PT USA 11:00am China | Total 180 Minutes | End | Final Recording Full Event deck / recording |
Q&A
Speaker | Question | Answer |
---|---|---|
Welcome | ||
Ti Zhou | How many models in the PaddlePaddle model zoo? How many in ONNX format? | |
Sheng Zha | Please remind where to find information on upcoming ONNX SC elections? | |
Joohoon Lee | What is the best way to get started learning about the ONNX roadmap, and getting involved? | |
Community Talks | ||
Han Zhao (GraphCore-China) | Are an performance benchmarks available on ML Perf/ML Commons? | |
Fengwei Yu (SenseTime-China) | ||
Tom Wildenhain (Microsoft-USA) and Scott McKay (Microsoft-Australia) | Are any ONNX models being run a lot on smartphones today that you know of? | |
Wranky Wang (Baidu-China) | Are there plans to put PaddlePaddle into open governance in LF AI & Data? | |
Rohit Sharma (AITechSystems-USA_CA) | How many of the models in ONNX model zoo have you compiled onto tinyml devices using DeepC? of the 36, have 2-3 been compiled? on what device? | Over 50 ONNX models have been compiled. We do not keep the record of the source of those ONNX models, so we can't comment on how many of them come from ONNX model zoo. Some of them are available in cAInvas gallery. deepSea supports most RISC and CISC devices. Cortex M4 based boards like Arduino Nano is one of the popular ones in the gallery. |
Krishna Gade (FiddlerAI-USA_CA) | Why is model versioning a big problem? Of the models in the ONNX model zoo, which are black box and which are explainable, from a Fiddler perspective? | |
Philippe Dooze (Orange-France) (picture) | Who are the biggest users of Acumos today? | |
Leon Wang (Huawei-China) | Are any unique models in the ONNX model zoo currently being developed with Mindspore? | |
Peng Wang (Microsoft China) | What are the challenges of building an training graph from existing ONNX models in the ONNX model zoo? | |
Speakers: Haihao Shen (Intel - China) and Saurabh Tangri (Intel) Contact: Rajeev Nalawadi (Intel-China) | Is LPOT open source? https://github.com/intel/lpot Are there plans to move it to LF AI & Data? | |
SIG Talks | ||
Ashwini Khade (Microsoft) and Jacky Chen (Microsoft) | ||
Michał Karzyński (Intel) and G. Ramalingam (Microsoft) | ||
Guenther Schmuelling (Microsoft), Kevin Chen (Nvidia), Chin Huang (IBM) | ||
Model Zoo/Tutorials SIG Update Co-Chair: Wenbing Li (Microsoft)(picture) | When do you think the number of models in the ONNX model zoo will be much greater than the number of ONNX operators? |
Additional Community Submissions not in main program - not covered online, but thank-you to submitters who can upload deck and prerecording for community to review at their leisure
Session | Deck / Prerecording (Links) |
---|---|
My experience implementing ONNX import for GAP processors | |
How we are making it insanely easy to deploy ml/ai models from jetson nano to Azure with ONNX Contact: Mahesh Yadav (Microsoft) | deck / prerecording |
Visualizing ONNX models’ internal data: Key things to look for? Contact: Mina Amiri (Zetane) | |
Deploying 3rd Party Models in PaddlePaddle via X2Paddle Converter | deck / prerecording |
TBD Contact: Emad Barsoum (Cerebras) | deck / prerecording |
Survey to be mailed to all who registered for the event
Thanks again for registering for the LF AI & Data Day – ONNX online virtual meetup! The recordings for each session are on the ONNX playlist of LF AI & Data Youtube, as well as the Event Wiki.
Please take a five minutes to share your feedback on the event.
On a scale of 1 (not helpful) to 5(very helpful) please rate the following:
Welcome and Opening Session: ONNX Progress and Update
Response: Rating 1-5
Ten Community Presentations
Response: Rating 1-5
Four SIG Presentations
Response: Rating 1-5
Post-Event Online Materials (Recordings, Presentations)
Response: Rating 1-5
Any additional feedback on this event and/or what you would like to see in future events?
Response: Text