Shanghai, China
June 24–26, 2019
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Tuesday, June 25 • 19:25 - 19:45
A Method for the Cost Optimization of Kubernetes-based Deep Learning Training and Inference - Pavee Han & Lei Wang, Tencent Cloud

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To improve the throughput capacity of the training or inference applications without adding extra GPU cores, we share one GPU core between multiple deep learning workloads in a kubernetes cluster by container-level virtual GPU technology. This technology has a better application prospect in the production environments because of its performance loss is lower than virtual-machine-level GPU virtualization.


Lei Wang

Senior Engineer, Tencent Cloud

Pavee Han

Senior Product Manager, Tencent Cloud

Tuesday June 25, 2019 19:25 - 19:45 CST
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