Optimizing Execution Time and Costs of Cross-Silo Federated Learning Applications with Datasets on different Cloud Providers-Reference-Cited by-同舟云学术

Optimizing Execution Time and Costs of Cross-Silo Federated Learning Applications with Datasets on different Cloud Providers

Published:2022-11 Issue: Volume: Page:
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Container-title:2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)
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Author:

Brum Rafaela C.¹,Sens Pierre²,Arantes Luciana²,Castro Maria Clicia³,de A. Drummond Lucia Maria¹

Affiliation:

1. Fluminense Federal University Institute of Computing,Niterói,Brazil

2. Sorbonne Université, CNRS, INRIA, LIP6,Paris,France

3. State University of Rio de Janeiro Institute of Mathematics and Statistics,Rio de Janeiro,Brazil

Funder

CNPq

Coordenação de Aperfeiçoamento de Pessoal de Ní vel Superior (CAPES)

Publisher

IEEE

Link

Reference30 articles.

1. Observing the clouds: a survey and taxonomy of cloud monitoring;ward;Journal of cloud computing,2014

5. Federated learning on non-iid data silos: An experimental study;li;ArXiv,2021

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