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Federica Filippini
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2020 – today
- 2025
- [j4]Roberto Sala
, Bruno Guindani
OSCAR-P and aMLLibrary: Profiling and predicting the performance of FaaS-based applications in computing continua. J. Syst. Softw. 221: 112282 (2025) - [c10]Federica Filippini
ML-Based Performance Modeling in Edge FaaS Systems. ESOCC 2025: 112-127 - 2024
- [j3]Federica Filippini
A Stochastic Approach for Scheduling AI Training Jobs in GPU-Based Systems. IEEE Trans. Cloud Comput. 12(1): 53-69 (2024) - [j2]Hamta Sedghani
SPACE4AI-D: A Design-Time Tool for AI Applications Resource Selection in Computing Continua. IEEE Trans. Serv. Comput. 17(6): 4324-4339 (2024) - [c9]Roberto Sala, Federica Filippini, Danilo Ardagna, Daniele Lezzi, Francesc Lordan, Patrick Thiem:
Greening AI: A Framework for Energy-Aware Resource Allocation of ML Training Jobs with Performance Guarantees. AINA (5) 2024: 110-121 - [i2]Roberto Sala, Bruno Guindani, Enrico Galimberti, Federica Filippini, Hamta Sedghani, Danilo Ardagna, Sebastián Risco, Germán Moltó, Miguel Caballer:
OSCAR-P and aMLLibrary: Profiling and Predicting the Performance of FaaS-based Applications in Computing Continua. CoRR abs/2411.07687 (2024) - 2023
- [j1]Federica Filippini
A Path Relinking Method for the Joint Online Scheduling and Capacity Allocation of DL Training Workloads in GPU as a Service Systems. IEEE Trans. Serv. Comput. 16(3): 1630-1646 (2023) - [c8]Federica Filippini
Performance Models for Distributed Deep Learning Training Jobs on Ray. SEAA 2023: 30-35 - [c7]Federica Filippini
SPACE4AI-R: a Runtime Management Tool for AI Applications Component Placement and Resource Scaling in Computing Continua. UCC 2023: 28 - [c6]Abednego Wamuhindo Kambale
Runtime Management of Artificial Intelligence Applications for Smart Eyewears. UCC 2023: 31 - [c5]Federica Filippini
FIGARO: reinForcement learnInG mAnagement acRoss the computing cOntinuum. UCC 2023: 47 - [c4]Enrico Galimberti
OSCAR-P and aMLLibrary: Performance Profiling and Prediction of Computing Continua Applications. ICPE (Companion) 2023: 139-146 - 2021
- [c3]Hamta Sedghani
A Random Greedy based Design Time Tool for AI Applications Component Placement and Resource Selection in Computing Continua. EDGE 2021: 32-40 - [c2]Federica Filippini
ANDREAS: Artificial intelligence traiNing scheDuler foR accElerAted resource clusterS. FiCloud 2021: 388-393 - [i1]Federica Filippini, Danilo Ardagna, Marco Lattuada
ANDREAS: Artificial intelligence traiNing scheDuler foR accElerAted resource clusterS. CoRR abs/2105.05080 (2021) - 2020
- [c1]Federica Filippini
Hierarchical Scheduling in on-demand GPU-as-a-Service Systems. SYNASC 2020: 125-132
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