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Neural Network Learning and Optimization (NNLO)
With deep neural networks becoming an essential tool for practitioners in academia, scaling them to accommodate the extensive amount of data without introducing a time trade-off is a constantly growing issue. Consequently, the ultimate goal of this project is to assist practitioners here at CERN to...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
2022
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2825242 |
Sumario: | With deep neural networks becoming an essential tool for practitioners in academia, scaling them to accommodate the extensive amount of data without introducing a time trade-off is a constantly growing issue. Consequently, the ultimate goal of this project is to assist practitioners here at CERN to scale their deep learning projects. The project involves developing a library that offers abstract modules for users to distribute their training and make use of the available computing resources without needing to worry about the technical details in the background. |
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