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Thursday, May 23 • 16:45 - 17:20
GPU Sharing for Machine Learning Workload on Kubernetes - Henry Zhang & Yang Yu, VMware

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Machine learning is becoming more and more popular in the technology world. The community is beginning to leverage Kubernetes to deploy and manage the machine learning workload.

One of the key challenges is to schedule the GPU-intensive workload. The Kubernetes has included GPU support for applications. However, there are some limitations of GPU usage:

1. GPU assignment is exclusive. Containers cannot share GPU resources.
2. A container can request one or more GPUs, but it is not possible to request a fraction of a GPU.

This session introduces how to run workload using the GPU in Kubernetes. In addition, an approach will be demonstrated to use virtual GPU (vGPU) technology to enable multiple pods concurrently accessing the same physical GPU. This approach not only increases the utilization of GPU resources, it also allows more GPU workloads to be scheduled on the same physical GPU.
Speakers
avatar for Henry Zhang

Henry Zhang

FATE TSC member, VMware
Haining Henry Zhang is a Technical Director at VMware China R&D, where he leads the development and incubation of projects on emerging technologies such as AI/ML, cloud native applications, and blockchain. He is the founder of CNCF's graduated project, Harbor, and currently serves... Read More →
avatar for Yang Yu

Yang Yu

Software Engineer, VMware
Yang is a staff engineer of China R&D, VMware. She's working on Kubernetes CNI plugin, focusing on providing CNI plugin for VMware NSX transformers product. Before joining in the Kubernetes community, Yang worked for OpenStack open source project for 4 years. She was familiar with... Read More →

KubeConEurope2019GPUSharingV1.3 pdf
Thursday May 23, 2019 16:45 - 17:20 CEST
Hall 8.0 C1
  Machine Learning + Data