Editing Academia Industry Engagement

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==	Academic and Industry Engagement - Workstream #10==
[https://www.opencompute.org/wiki/Time_Appliance_Project Back to Time Appliances Project's wiki]

==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.

==Organization==

	· Identify and distribute key research areas in time synchronization.

	· Organize virtual meetings to bring together researchers and industry practitioners to discuss and demo current challenges and novel solutions.

	· Top submission can present at OCP conference or recommended to other conferences.

	· Create a central repository for research findings, papers, presentations and best practices related to time synchronization (OCP-TAP wiki for this)

==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: [mailto:Dan.Biderman@intel.com Dan Biderman] (Intel)
:- Lead: [mailto:helbakoury@gmail.com.com Hesham Albakoury] (Individual)

==Bi-Weekly Meeting Invite==
11:00am - 11:55am PT Bi-Weekly Wednesday meetings (opposites weeks of the normal OCP-TAP meeting) : [https://teams.microsoft.com/dl/launcher/launcher.html?url=%2F_%23%2Fl%2Fmeetup-join%2F19%3Ameeting_OGE1MzNkMGMtZDRjMS00YzFiLTg4MTAtZjcxNzEwYzI2ODIy%40thread.v2%2F0%3Fcontext%3D%257b%2522Tid%2522%253a%2522fbb4e2fb-f802-4d55-beca-b7149551e928%2522%252c%2522Oid%2522%253a%2522cff27e02-befc-4437-98d5-96034f77b90c%2522%257d%26anon%3Dtrue&type=meetup-join&deeplinkId=5f0bbd41-a286-4e8b-b786-5162812cfe21&directDl=true&msLaunch=true&enableMobilePage=true&suppressPrompt=true Launch Teams Meeting Link]

==Recording from Past Calls==
Wednesday May 1st 2024 Work Stream Introduction [https://drive.google.com/file/d/1Ctz2eWt2e71y9ChquZGdu6Fc9H5PQZZs/view?usp=sharing 20 Jan 2022]

===Zoom Details===

Meeting ID: 810 8874 0168

Passcode: 760037

==Projects==

{| class="wikitable"
|- 
!
! 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==
{| class="wikitable"
|- 
!
! Paper !! Link 
|- 
| '''#1'''
| TBD
| TBD
|-
|}

==Demos==

{| class="wikitable"
|- 
!
! Demo Title !! Video Link 
|- 
| '''#1'''
| TBD
| TBD
|-
|- 
|}