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2020 – today
- 2024
[j14]Martin Molan
, Mohsen Seyedkazemi Ardebili, Junaid Ahmed Khan, Francesco Beneventi, Daniele Cesarini, Andrea Borghesi, Andrea Bartolini:
GRAAFE: GRaph Anomaly Anticipation Framework for Exascale HPC systems. Future Gener. Comput. Syst. 160: 644-653 (2024)- [j13]Emmen Farooq, Michela Milano, Andrea Borghesi:
Harnessing federated learning for anomaly detection in supercomputer nodes. Future Gener. Comput. Syst. 161: 673-685 (2024) - [c36]Lorenzo Tribuiani, Luca Giuliani, Allegra De Filippo, Andrea Borghesi:
Expert-MusiComb: Injective Domain Knowledge in a Neuro-Symbolic Approach for Music Generation. CREAI@ECAI 2024: 46-58 - 2023
- [j12]Gregor Molan, Gregor Dolinar, Jovan Bojkovski, Radu Prodan, Andrea Borghesi, Martin Molan:
Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product. IEEE Access 11: 115599-115616 (2023) - [j11]Martin Molan, Andrea Borghesi, Daniele Cesarini, Luca Benini, Andrea Bartolini:
RUAD: Unsupervised anomaly detection in HPC systems. Future Gener. Comput. Syst. 141: 542-554 (2023) - [j10]Andrea Borghesi, Alessio Burrello, Andrea Bartolini:
ExaMon-X: A Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems. IEEE Internet Things J. 10(4): 2995-3005 (2023) - [c35]Luca Giuliani, Allegra De Filippo, Andrea Borghesi:
Towards Intelligent Music Production: A Sample-based Approach. CREAI@AI*IA 2023: 50-59 - [c34]Francesco Antici, Andrea Borghesi, Zeynep Kiziltan:
Online Job Failure Prediction in an HPC System. Euro-Par Workshops 2023: 167-179 - [c33]Matteo Francobaldi, Allegra De Filippo, Andrea Borghesi, Nikola Pizurica, Igor Jovancevic, Tim Llewellynn, Miguel de Prado:
TinderAI: Support System for Matching AI Algorithms and Embedded Devices. FLAIRS 2023 - [c32]Luca Giuliani, Francesco Ballerini, Allegra De Filippo, Andrea Borghesi:
MusiComb: a Sample-based Approach to Music Generation Through Constraints. ICTAI 2023: 194-198 - [c31]Emmen Farooq, Andrea Borghesi:
A Federated Learning Approach for Anomaly Detection in High Performance Computing. ICTAI 2023: 496-500 - [c30]Allegra De Filippo, Luca Giuliani, Eleonora Mancini, Andrea Borghesi, Paola Mello, Michela Milano:
Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations. IJCAI 2023: 5806-5814 - [c29]Martin Molan, Junaid Ahmed Khan, Andrea Borghesi, Andrea Bartolini:
Graph Neural Networks for Anomaly Anticipation in HPC Systems. ICPE (Companion) 2023: 239-244 - [d13]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset: time-aggregated data for anomaly detection. Zenodo, 2023
- [d12]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 1: from 20-03 to 20-12. Zenodo, 2023 - [d11]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 2: from 21-01 to 21-06. Zenodo, 2023 - [d10]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 3: from 21-07 to 21-09. Zenodo, 2023 - [d9]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 4: from 21-10 to 21-12. Zenodo, 2023 - [d8]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 5: from 22-01 to 22-02. Zenodo, 2023 - [d7]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 6: 22-03. Zenodo, 2023 - [d6]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 7: 22-04. Zenodo, 2023 - [d5]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 8: 22-05. Zenodo, 2023 - [d4]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 9: 22-06. Zenodo, 2023 - [d3]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 10: 22-07. Zenodo, 2023 - [d2]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 11: 22-08. Zenodo, 2023 - [d1]Andrea Borghesi, Carmine Di Santi, Martin Molan, Mohsen Seyedkazemi Ardebili, Alessio Mauri, Massimiliano Guarrasi, Daniela Galetti, Mirko Cestari, Francesco Barchi, Luca Benini, Francesco Beneventi, Andrea Bartolini:
M100 dataset 12: 22-09. Zenodo, 2023 - [i17]W. A. Ahmad, Andrea Bartolini, Francesco Beneventi, Luca Benini, Andrea Borghesi, Marco Cicala, Privato Forestieri, Cosimo Gianfreda, Daniele Gregori, Antonio Libri, Filippo Spiga, Simone Tinti:
Design of an energy aware petaflops class high performance cluster based on power architecture. CoRR abs/2307.05790 (2023) - [i16]Francesco Antici, Andrea Borghesi, Zeynep Kiziltan:
Online Job Failure Prediction in an HPC System. CoRR abs/2308.15481 (2023) - 2022
- [j9]Andrea Borghesi, Diego Di Salvo, Pietro Ciolli, Teresa Falcone, Marco Ravanelli, Davide Farina, Nicola Carapella:
Detection Rate and Variability in Measurement of Mandibular Incisive Canal on Cone-Beam Computed Tomography: A Study of 220 Dentate Hemi-Mandibles from Italy. J. Imaging 8(6): 161 (2022) - [j8]Allegra De Filippo, Andrea Borghesi, Andrea Boscarino, Michela Milano:
HADA: An automated tool for hardware dimensioning of AI applications. Knowl. Based Syst. 251: 109199 (2022) - [j7]Andrea Borghesi, Martin Molan, Michela Milano, Andrea Bartolini:
Anomaly Detection and Anticipation in High Performance Computing Systems. IEEE Trans. Parallel Distributed Syst. 33(4): 739-750 (2022) - [c28]Luca Giuliani, Allegra De Filippo, Andrea Borghesi, Paola Mello, Michela Milano:
A Multi-modal Perspective for the Artistic Evaluation of Robotic Dance Performances. CREAI@AI*IA 2022: 84-93 - [c27]Martin Molan, Andrea Borghesi, Luca Benini, Andrea Bartolini:
Semi-supervised anomaly detection on a Tier-0 HPC system. CF 2022: 203-204 - [c26]Allegra De Filippo, Andrea Borghesi:
Constrained Hardware Dimensioning for AI Algorithms. PAIS@ECAI 2022: 145-148 - [c25]Martin Molan, Andrea Borghesi, Luca Benini, Andrea Bartolini:
Analysing Supercomputer Nodes Behaviour with the Latent Representation of Deep Learning Models. Euro-Par 2022: 171-185 - [c24]Martin Molan, Andrea Borghesi, Luca Benini, Andrea Bartolini:
Machine Learning Methodologies to Support HPC Systems Operations: Anomaly Detection. Euro-Par Workshops 2022: 294-298 - [c23]Bassem Hichri, Anass Driate, Andrea Borghesi, Francesco Giovannini:
Predictive Maintenance Based on Machine Learning Model. AIAI (2) 2022: 250-261 - [i15]Stefano Teso, Laurens Bliek, Andrea Borghesi, Michele Lombardi, Neil Yorke-Smith, Tias Guns, Andrea Passerini:
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. CoRR abs/2205.10157 (2022) - [i14]Martin Molan, Andrea Borghesi, Daniele Cesarini, Luca Benini, Andrea Bartolini:
RUAD: unsupervised anomaly detection in HPC systems. CoRR abs/2208.13169 (2022) - 2021
- [j6]Alberto Signoroni, Mattia Savardi, Sergio Benini, Nicola Adami, Riccardo Leonardi, Paolo Gibellini, Filippo Vaccher, Marco Ravanelli, Andrea Borghesi, Roberto Maroldi, Davide Farina:
BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset. Medical Image Anal. 71: 102046 (2021) - [c22]Andrea Borghesi, Giuseppe Di Modica, Paolo Bellavista, Varun Gowtham, Alexander Willner, Daniel Nehls, Florian Kintzler, Stephan Cejka, Simone Rossi Tisbeni, Alessandro Costantini, Matteo Galletti, Marica Antonacci, Jean Christian Ahouangonou:
IoTwins: Design and Implementation of a Platform for the Management of Digital Twins in Industrial Scenarios. CCGRID 2021: 625-633 - [c21]Martin Molan, Andrea Borghesi, Francesco Beneventi, Massimiliano Guarrasi, Andrea Bartolini:
An Explainable Model for Fault Detection in HPC Systems. ISC Workshops 2021: 378-391 - [i13]Federico Baldo, Lorenzo Dall'Olio, Mattia Ceccarelli, Riccardo Scheda, Michele Lombardi, Andrea Borghesi, Stefano Diciotti, Michela Milano:
Deep Learning for Virus-Spreading Forecasting: a Brief Survey. CoRR abs/2103.02346 (2021) - 2020
- [j5]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
A machine learning approach to online fault classification in HPC systems. Future Gener. Comput. Syst. 110: 1009-1022 (2020) - [j4]Daniele Cesarini, Andrea Bartolini, Andrea Borghesi, Carlo Cavazzoni, Mathieu Luisier, Luca Benini:
Countdown Slack: A Run-Time Library to Reduce Energy Footprint in Large-Scale MPI Applications. IEEE Trans. Parallel Distributed Syst. 31(11): 2696-2709 (2020) - [c20]Andrea Borghesi, Giuseppe Tagliavini, Michele Lombardi, Luca Benini, Michela Milano:
Combining learning and optimization for transprecision computing. CF 2020: 10-18 - [c19]Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano:
Injective Domain Knowledge in Neural Networks for Transprecision Computing. LOD (1) 2020: 587-600 - [c18]Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano:
An Analysis of Regularized Approaches for Constrained Machine Learning. TAILOR 2020: 112-119 - [i12]Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano:
Injective Domain Knowledge in Neural Networks for Transprecision Computing. CoRR abs/2002.10214 (2020) - [i11]Andrea Borghesi, Giuseppe Tagliavini, Michele Lombardi, Luca Benini, Michela Milano:
Combining Learning and Optimization for Transprecision Computing. CoRR abs/2002.10890 (2020) - [i10]Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano:
An Analysis of Regularized Approaches for Constrained Machine Learning. CoRR abs/2005.10674 (2020) - [i9]Andrea Borghesi, Federico Baldo, Michela Milano:
Improving Deep Learning Models via Constraint-Based Domain Knowledge: a Brief Survey. CoRR abs/2005.10691 (2020) - [i8]Alberto Signoroni, Mattia Savardi, Sergio Benini, Nicola Adami, Riccardo Leonardi, Paolo Gibellini, Filippo Vaccher, Marco Ravanelli, Andrea Borghesi, Roberto Maroldi, Davide Farina:
End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays. CoRR abs/2006.04603 (2020) - [i7]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
A Machine Learning Approach to Online Fault Classification in HPC Systems. CoRR abs/2007.14241 (2020)
2010 – 2019
- 2019
- [j3]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems. Eng. Appl. Artif. Intell. 85: 634-644 (2019) - [j2]Andrea Borghesi, Andrea Bartolini, Michela Milano, Luca Benini:
Pricing schemes for energy-efficient HPC systems: Design and exploration. Int. J. High Perform. Comput. Appl. 33(4) (2019) - [c17]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection Using Autoencoders in High Performance Computing Systems. AAAI 2019: 9428-9433 - [c16]Andrea Borghesi, Antonio Libri, Luca Benini, Andrea Bartolini:
Online Anomaly Detection in HPC Systems. AICAS 2019: 229-233 - [c15]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection using Autoencoders in High Performance Computing Systems. DDC@AI*IA 2019: 24-32 - [c14]Andrea Borghesi, Michela Milano, Luca Benini:
Frequency Assignment in High Performance Computing Systems. AI*IA 2019: 151-164 - [c13]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
Online Fault Classification in HPC Systems Through Machine Learning. Euro-Par 2019: 3-16 - [c12]Andrea Bartolini, Francesco Beneventi, Andrea Borghesi, Daniele Cesarini, Antonio Libri, Luca Benini, Carlo Cavazzoni:
Paving the Way Toward Energy-Aware and Automated Datacentre. ICPP Workshops 2019: 8:1-8:8 - [i6]Andrea Borghesi, Antonio Libri, Luca Benini, Andrea Bartolini:
Online Anomaly Detection in HPC Systems. CoRR abs/1902.08447 (2019) - [i5]Daniele Cesarini, Andrea Bartolini, Andrea Borghesi, Carlo Cavazzoni, Mathieu Luisier, Luca Benini:
COUNTDOWN Slack: a Run-time Library to Reduce Energy Footprint in Large-scale MPI Applications. CoRR abs/1909.12684 (2019) - 2018
- [j1]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Scheduling-based power capping in high performance computing systems. Sustain. Comput. Informatics Syst. 19: 1-13 (2018) - [c11]Andrea Bartolini, Andrea Borghesi, Antonio Libri, Francesco Beneventi, Daniele Gregori, Simone Tinti, Cosimo Gianfreda, Piero Altoe:
The D.A.V.I.D.E. big-data-powered fine-grain power and performance monitoring support. CF 2018: 303-308 - [c10]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
FINJ: A Fault Injection Tool for HPC Systems. Euro-Par Workshops 2018: 800-812 - [c9]Matthias Maiterth, Gregory A. Koenig, Kevin T. Pedretti, Siddhartha Jana, Natalie J. Bates, Andrea Borghesi, Dave Montoya, Andrea Bartolini, Milos Puzovic:
Energy and Power Aware Job Scheduling and Resource Management: Global Survey - Initial Analysis. IPDPS Workshops 2018: 685-693 - [i4]Andrea Borghesi, Andrea Bartolini, Michela Milano, Luca Benini:
Pricing Schemes for Energy-Efficient HPC Systems: Design and Exploration. CoRR abs/1806.05135 (2018) - [i3]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
FINJ: A Fault Injection Tool for HPC Systems. CoRR abs/1807.10056 (2018) - [i2]Alessio Netti, Zeynep Kiziltan, Özalp Babaoglu, Alina Sîrbu, Andrea Bartolini, Andrea Borghesi:
Online Fault Classification in HPC Systems through Machine Learning. CoRR abs/1810.11208 (2018) - [i1]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Anomaly Detection using Autoencoders in High Performance Computing Systems. CoRR abs/1811.05269 (2018) - 2017
- [b1]Andrea Borghesi:
Power-Aware Job Dispatching in High Performance Computing Systems. University of Bologna, Italy, 2017 - [c8]Wissam Abu Ahmad, Andrea Bartolini, Francesco Beneventi, Luca Benini, Andrea Borghesi, Marco Cicala, Privato Forestieri, Cosimo Gianfreda, Daniele Gregori, Antonio Libri, Filippo Spiga, Simone Tinti:
Design of an Energy Aware Petaflops Class High Performance Cluster Based on Power Architecture. IPDPS Workshops 2017: 964-973 - [c7]Cristian Galleguillos, Alina Sîrbu, Zeynep Kiziltan, Özalp Babaoglu, Andrea Borghesi, Thomas Bridi:
Data-Driven Job Dispatching in HPC Systems. MOD 2017: 449-461 - 2016
- [c6]Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini:
Predictive Modeling for Job Power Consumption in HPC Systems. ISC 2016: 181-199 - 2015
- [c5]Valerio Iachini, Andrea Borghesi, Michela Milano:
Agent Based Simulation of Incentive Mechanisms on Photovoltaic Adoption. AI*IA 2015: 136-148 - [c4]Andrea Borghesi, Francesca Collina, Michele Lombardi, Michela Milano, Luca Benini:
Power Capping in High Performance Computing Systems. CP 2015: 524-540 - [c3]Andrea Borghesi, Christian Conficoni, Michele Lombardi, Andrea Bartolini:
MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot! HPCS 2015: 88-95 - 2014
- [c2]Andrea Bartolini, Andrea Borghesi, Thomas Bridi, Michele Lombardi, Michela Milano:
Proactive Workload Dispatching on the EURORA Supercomputer. CP 2014: 765-780 - 2013
- [c1]Andrea Borghesi, Michela Milano, Marco Gavanelli, Tony Woods:
Simulation Of Incentive Mechanisms For Renewable Energy Policies. ECMS 2013: 32-38
Coauthor Index
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