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17 May 2022
Valencia, Spain
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Please note: This schedule is automatically displayed in Central European Standard Time, UTC +2. To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date."  The schedule is subject to change.


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Pre-record [clear filter]
Tuesday, May 17
 

11:00 CEST

Empower Heterogeneous Edge AI Acceleration with K8s - Tiejun Chen & Zitong Xu, VMware
As an emerging trend in the area of edge computing, edge workloads tend to be managed and orchestrated by k8s. In the meantime, as the the top one workload of edge computing, edge AI accelerations have been enabled by different vendors' edge AI accelerators quickly, including Nvidia edge GPU series, Intel Movidius VPU, Google edge TPU, etc. Actually you can see many ASIC-based edge AI accelerators and even some high-end CPUs used in edge AI. Obviously, edge users have the challenges around empowering these heterogeneous edge AI on the edge with upstream k8s or those edge k8s versions due to missing a general unified framework on k8s. Here we'd like to introduce our unified framework as a plugin to k8s with the following key mechanisms - 1. Extend the Node Feature Discovery to detect edge AI accelerators automatically 2. Unify different vendors' device plugin to provision work nodes according to it's own edge AI accelerator 3. Introduce transparent backend accelerations to boost ML upstream frameworks such as Tensorflow, Pytorch, etc 4. Attaching remote GPU to edge In our project we provide a unified edge AI framework to help k8s empower heterogeneous AI acceleration on the edge.

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Speakers
avatar for Tiejun Chen

Tiejun Chen

Technical Leader & Architect, VMware
Tiejun Chen is one technical leader and Architect from ATG, Advanced Technology Group, VMware OCTO. Before joined VMware, he ever worked at Wind River System Linux and Intel OTC - Opensource Technology Center. He ever made many presentations at kubecon China 2021, LC3 China 2017... Read More →
ZX

Zitong Xu

Developer, VMware
Zitong Xu is from VMware OCTO - ATG. She is the core developer specific to machine learning and k8s, and many experiences of building edge computing with the partners and the customers.


Tuesday May 17, 2022 11:00 - 11:30 CEST
Pavilion 4, Room C | Level 2 | Central Forum

11:50 CEST

Lightning Talk: Join the Cloud Native Journey to Shuttle Back and Forth Applications Across Edges - Ruoyu Ying & Qiang Ren, Intel
SD-WAN handles the network connectivity issues between distributed applications in a seamless, secure and efficient manner through replacing traditional branch routers with virtualized or appliance-based software. However, as the concept of edge prevails recently, distributed applications are usually deployed across multiple resource-constrained k8s edges. Then how to expose the services and manage the connections between in a cloud native way becomes a critical issue for users. The open-source project SD-EWAN under the Akraino community’s ICN blueprint is definitely a comprehensive solution. Its CNF, which integrated with multiple network functions based on OpenWRT, is able to serve the distributed applications with secure connections and easy management against networking and the CNF can be automatically thru the overlay controller within SD-EWAN to achieve multi-edge collaboration. This session will show the basic architecture how SDEWAN utilizing k8s to help with the network connections across applications live in different edges, and a demo to showcase its usage for cross-edge collaboration (e.g. advanced load-balancing with service mesh).

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Speakers
avatar for Ruoyu Ying

Ruoyu Ying

Cloud Orchestration Software Engineer, Intel
Ruoyu Ying is a cloud orchestration software engineer from Cloud Software Engineering, department of SATG, Intel. She joined Intel after achieved her master degree from Hong Kong University majoring in Computer Science and have worked as a key contributor and committer of VFC project... Read More →
avatar for Qiang Ren

Qiang Ren

Cloud Orchestration Software Engineer, Intel
Ren Qiang works as a Cloud Orchestration Software Engineer in SATG, Intel. He mainly focuses on Cloud Native technologies in the edge computing domain and is the key contributor to the SD-EWAN project under Akraino community. At the same time, he actively participates in open source... Read More →


Tuesday May 17, 2022 11:50 - 12:00 CEST
Pavilion 4, Room C | Level 2 | Central Forum

16:10 CEST

Building a Multi-Node Cluster with K3s Using ARM Devices - Sergio Méndez, Universidad de San Carlos de Guatemala
Edge computing is coming as a way to improve user experience for applications, processing data near to the source. Sometimes in edge computing you share data between local machines and the cloud. If you are starting an edge computing project, you could be interested in taking advantage of containers on the edge. Here is where K3s shines to implement edge computing solutions on low resources environments that commonly use ARM devices. In this talk we are going to explore the key elements and best practices to build a K3s cluster on the edge using ARM devices. The talk will show how to build this cluster using Raspberry devices, showing how to configure your local network and a bare metal load balancer with MetalLB, and install other cloud native storage blocks such as Longhorn or OpenEBS. This to finally get a production ready K3s cluster. The talk also provides a quickstart to build edge computing environments for your needs, mentioning different use cases and challenges of this kind when building edge solutions.

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Speakers
avatar for Sergio Méndez

Sergio Méndez

Serverless functions at the edge using Knative and K3s, Universidad de San Carlos de Guatemala
Sergio Méndez is a systems engineer and professor of operating systems at San Carlos of Guatemala university. His work at the university is related to teaching and researching cloud native technologies with his students. He has experience working on DevOps, and MLOps using open source... Read More →



Tuesday May 17, 2022 16:10 - 16:40 CEST
Pavilion 4, Room C | Level 2 | Central Forum
 
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