You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 36 Next »

ai (1).pptx Blueprint species:

Use Case Attributes

Description

Informational

Type

New Blueprint for AI on the Edge

 

Blueprint Family

Integrated Edge Cloud (IEC)

 

Use Case

Safety, security, and surveillance

 

Blueprint proposed Name

AI on the edge

 

Initial POD Cost (capex)

Leverage Unicycle P

 

Scale & Type

One per community

 

Applications

Training deep learning models for IoT devices

 

Power and memory restrictions

IoT devices are power and memory constrained.

 

Infrastructure orchestration

Need IoT device ID 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 data streams) and server/client (a database for trained models in binary format)

 

DataplaneVPP

Workload Type

  • Containers (Tensoflow, Keras containers)
  • VMs

 

Additional Details

There are mainly 4 pieces:

  1. a database to collect raw data streams
  2. tons of containers with various models on training
  3. a database for trained models in binary format, and predicted result in JSON format
  4. a database for queries records and transactions of database mentioned in 1 and 3.

 


Attachment: 

Akraino_Blueprint_Integrated_Edge_Cloud_AI.pptx

Committer

Affiliation

 Committer Contact Info

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)

Gang Chen

Baidu

chengang13@baidu.com




Hechun ZhangBaiduzhanghechun@baidu.com


Dechao KongBaidukongdechao@baidu.com


Arm



PSU




N
Raviraj MahatmeArmraviraj.mahatme@arm.com



Contributor

Affiliation

 Committer Contact Info

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)



















  • No labels