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20242026
most citedOSCAR-P and aMLLibrary: Profiling and Predicting the Performance of FaaS-based Applications in Computing Continua

5 citations · 5 across the 4 of their papers we have counts for

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cs.PF2024★ 5 cited

OSCAR-P and aMLLibrary: Profiling and Predicting the Performance of FaaS-based Applications in Computing Continua

Roberto Sala, Bruno Guindani, Enrico Galimberti +6

This paper proposes an automated framework for efficient application profiling and training of Machine Learning (ML) performance models, composed of two parts: OSCAR-P and aMLLibra…

cs.DC2024

Efficient Parameter Tuning for a Structure-Based Virtual Screening HPC Application

Bruno Guindani, Davide Gadioli, Roberto Rocco +2

Virtual screening applications are highly parameterized to optimize the balance between quality and execution performance. While output quality is critical, the entire screening pr…