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Talk14 min

Training and Serving ML workloads with Kubeflow at CERN

Dejan Golubovic · CERN

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About

Machine Learning (ML) has been growing in popularity in multiple areas and groups at CERN, covering fast simulation, tracking, anomaly detection, among many others. We describe a new service available at CERN, based on Kubeflow and managing the full ML lifecycle: data preparation and interactive analysis, large scale distributed model training and model serving. We cover specific features available for hyper-parameter tuning and model metadata management, as well as infrastructure details to integrate accelerators and external resources. We also present results and a cost evaluation from scaling out a popular ML use case using public cloud resources, achieving close to linear scaling when using a large number of GPUs..

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The talk

  1. Training and Serving ML workloads with Kubeflow at CERN 2021-05-20 · 14 min · CERN's player

Credits and licence

Institution
CERN
Department
Conferences
Speaker
Dejan Golubovic
Year
2021
Language
English
Subjects
Physics, Computer science, Earth and environment
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
Who can watch
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