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DTSTART;TZID=America/Denver:20231113T094000
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UID:submissions.supercomputing.org_SC23_sess448_ws_canolt101@linklings.com
SUMMARY:Kubeflow-as-a-Service on HPC clusters – First Experiences
DESCRIPTION:Mohsin Ahmed Shaikh (King Abdullah University of Science and T
 echnology (KAUST)), Nasr Hussain and Islam Elmas (Brightskies Inc), and Sa
 ber Feki (King Abdullah University of Science and Technology (KAUST))\n\nD
 evelopment platforms specific to domain sciences has the potential to impr
 ove user's productivity on a HPC cluster by smoothing the steep learning c
 urve using it. These platforms also help abstracting certain practices the
  user must implement to get the optimal performance out of the allocated r
 esource. These objectives require pre-work, both on the systems side and a
 t the application level. The presentation discusses the first experiences 
 of prototyping with Kubeflow and deploying it as-a-service to be shared by
  multiple users. The deployment was designed with HPC cluster or multi-nod
 e cloud instances as target computational resources. Kubeflow is an openso
 urce platform to make deployment of ML/DL workloads easy. It depends on Ku
 bernetes. Kubeflow offers a simple UI for interactive computing, orchestra
 tion of workflows using Kubeflow pipeline, and an intuitive interface for 
 hyperparameter tuning experiments using Katib. These are attractive featur
 es when considering the ease of use in deploying software environments for
  model and workflow development for users in academic research settings on
  cloud and university HPC cluster.\n\nRegistration Category: Workshop Reg 
 Pass\n\nSession Chairs: Richard Shane Canon (Lawrence Berkeley National La
 boratory (LBNL)); Alberto Madonna (ETH Zürich, Swiss National Supercomputi
 ng Centre (CSCS)); Laurie A. Stephey (Lawrence Berkeley National Laborator
 y (LBNL), National Energy Research Scientific Computing Center (NERSC)); a
 nd Andrew Younge (Sandia National Laboratories)\n\n
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