Academia Industry Engagement

Academic and Industry Engagement - Workstream #10

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Goal

The Time Synchronization Industry-Academia Workstream (TSIAW) brings together researchers and industry practitioners to discuss and solve challenging problems in time synchronization of connected devices and applications.

Objectives

Bridge the gap between theory and practice

The TSIAW will act as a bridge between academic research and industry needs. By bringing together researchers and practitioners, the workstream will ensure that research efforts address real-world challenges faced by the ever-growing and complex data center and edge communication networks and devices by developing robust, reliable and scalable novel solutions

Synchronization Data for Decision Makers

Research and develop the data required by data center decision makers, on how to use precise time to make data center and edge applications (AI, Databases, Microservices, etc.) or portions of that software run 2x to 1000+x better in performance, power, latency and/or cost when compared to unsynchronized solution.

Develop Time Synchronization Projects

The TSIAW will expose projects for academia that will have impact on data center and edge technologies. When possible, TSIAW will help facilitating the research. When possible, making a community of time synchronization experts available to Academia and Industry to improve applications through time synchronization.

Advance the field of time synchronization

The TSIAW will strive to push the boundaries of time synchronization research by facilitating collaboration between industry and academia. This will involve identifying critical research areas, promoting joint research projects, and disseminating findings and solutions through conferences, workshops, repositories, and publications. (First virtually) (Not focused on crazy precise, more on applications)

Foster a dynamic, vibrant and knowledgeable community of time synchronization experts

The TSIAW will create a platform for communication and collaboration among industry professionals, academics, and researchers working on time synchronization

Project Team

- Lead: Dan Biderman (Intel)

- Lead: Hesham Albakoury (Individual)

Bi-Weekly Meeting Invite

11:00am - 11:55am PT Bi-Weekly Wednesday meetings (opposites weeks of the normal OCP-TAP meeting) : Launch Teams Meeting Link

Recording from Past Calls

Wednesday May 1st 2024 Work Stream Introduction 20 Jan 2022

Zoom Details

Meeting ID: 810 8874 0168

Passcode: 760037

Projects

	Start Date	End Date	Call For Action	Statement	Introduction Slides	Wiki
#1	5/1/2024	Open	Artificial Intelligence / Machine Learning College Project	A Precisely Synchronized Datacenter Would Improve Overall Performance of Distributed Artificial Intelligence and Machine Learning

References

	Paper	Link
#1	TBD	TBD

Demos

	Demo Title	Video Link
#1	TBD	TBD