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Kubeflow is maturing as a cloud native Machine Learning (ML) platform that simplifies the journey of development, deployment, and management of ML on Kubernetes. As Kubeflow gets increasingly adopted, practitioners are looking beyond functions and starting to explore its performance and cost efficiency in the real world. MLPerf is a state-of-the-art benchmark suite that aims to set an industry standard for end-to-end performance evaluation of ML systems with real-world workloads covering both training and inference phases of ML lifecycle. This talk will provide a brief overview about MLPerf, followed by detailed discussions about how MLPerf can be adapted to evaluate ML performance on Kubeflow and Kubernetes, as well as how the performance results can be leveraged to guide the future design and optimization of cloud native ML platforms based on Kubeflow and Kubernetes.
Xinyuan Huang is a Technical Leader at Cisco, where he leads the performance evaluations and optimizations in cloud and AI/ML systems. He is an active member in MLPerf and Kubeflow community.
Elvira Dzhuraeva is a AI/ML Technical Product Engineer at Cisco where she leads cloud and on-premise ML and AI strategy. She is a Technical Product Manager at Kubeflow and a member in MLPerf community.
Thursday August 20, 2020 18:05 - 18:40 CEST
InXpohttps://onlinexperiences.com/Launch/Event.htm?ShowKey99259
