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Complexity and Scale in AI-Assisted Workflow Management: A Federated Learning Case Study

Thareja, Komal et al.
arXiv (All) · Papers
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and-cluster-computingartificial-intelligencedistributedparallelsoftware-engineering
Federated learning over medical images is a demanding workflow application. Each round fans out across parallel client jobs and converges on an aggregation step that feeds the next round. At scale this yields 101 sub-workflows and 2,679 jobs on GPUs at four sites, which takes an expert months to bui
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