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Blueprint species:

Use Case Attributes

Description

Informational

Type

New

 

Blueprint Family

Integrated Edge Cloud (IEC)

 

Use Case

Safety and security, driving assistant

 

Blueprint proposed Name

IEC Type 3: Autonomous vehicles as the edge

 

Initial POD Cost (capex)

N/A

 

Scale & Type

One per vehicle

 

Applications

Video Processing for AutoDriving (especially training deep learning models)

  • lane guidance
  • safety and security applications
  • remote control

 

Power and memory restrictions

Autonoumous vehicles are power and memory constrained.

 

Infrastructure orchestration

Need Geolocation correlation with deep learning model (the trained ones in binary format)

 

SDN

Calico and K8s, and Containers serving as client/server (a database to collect raw videos/video streams) and server/client (a database for trained models in binary format)

 

Workload Type

  • Containers (Tensoflow, Keras containers)
  • VMs

 

Dataplane VPP w/ Direct GPU (e.g. GPUnet)

Additional Details

Different bus connection: Ethernet, CANbus, etc.

There are mainly 4 pieces:

  1. a database to collect raw videos/video streams
  2. tons of containers with various models on training
  3. a database for trained models in binary format
  4. a database for queries records and transactions of database mentioned in 1 and 3.

 



Committer

Committer

Company

 Committer Contact Info

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)

Didi





Arm



PSU




N



Proposed PTL: 

Ken Yi


Contributors: 

@soshun@soshun.arai@arm.com

Tina Tsou 

Wenhui Zhang


Committers: 

Ken Yi 

Tina Tsou


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