Francesco Di Natale

According to our database, Francesco Di Natale authored at least 11 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

An eXplainable Artificial Intelligence framework to predict marine scrubbers performances.

Luigi Piero Di Bonito, Lelio Campanile, Mauro Iacono, Francesco Di Natale

Eng. Appl. Artif. Intell., 2025

2024

Ensemble Models For Predicting CO Concentrations: Application And Explainability In Environmental Monitoring In Campania, Italy.

Lelio Campanile, Luigi Piero Di Bonito, Francesco Di Natale, Mauro Iacono

Proceedings of the 38th ECMS International Conference on Modelling and Simulation, 2024

2023

Prediction Of Chemical Plants Operating Performances: A Machine Learning Approach.

Lelio Campanile, Luigi Piero Di Bonito, Mauro Iacono, Francesco Di Natale

Proceedings of the 37th ECMS International Conference on Modelling and Simulation, 2023

2022

Enabling machine learning-ready HPC ensembles with Merlin.

J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom

Future Gener. Comput. Syst., 2022

DFMan: A Graph-based Optimization of Dataflow Scheduling on High-Performance Computing Systems.

Fahim Chowdhury, Francesco Di Natale, Adam Moody, Kathryn M. Mohror, Weikuan Yu

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

Scalable Composition and Analysis Techniques for Massive Scientific Workflows.

Dong H. Ahn, Xiaohua Zhang, Jeffrey Mast, Stephen Herbein, Francesco Di Natale, Dan Kirshner, Sam Ade Jacobs, Ian Karlin, Daniel J. Milroy, Bronis R. de Supinski, Brian Van Essen, Jonathan E. Allen, Felice C. Lightstone

Proceedings of the 18th IEEE International Conference on e-Science, 2022

2021

Generalizable coordination of large multiscale workflows: challenges and learnings at scale.

Harsh Bhatia, Francesco Di Natale, Joseph Y. Moon, Xiaohua Zhang, Joseph R. Chavez, Fikret Aydin, Christopher B. Stanley, Tomas Oppelstrup, Chris Neale, Sara Kokkila Schumacher, Dong H. Ahn, Stephen Herbein, Timothy S. Carpenter, Sandrasegaram Gnanakaran, Peer-Timo Bremer, James N. Glosli, Felice C. Lightstone, Helgi I. Ingólfsson

Proceedings of the International Conference for High Performance Computing, 2021

2020

Emulating I/O Behavior in Scientific Workflows on High Performance Computing Systems.

Fahim Chowdhury, Yue Zhu, Francesco Di Natale, Adam Moody, Elsa Gonsiorowski, Kathryn M. Mohror, Weikuan Yu

Proceedings of the Fifth IEEE/ACM International Parallel Data Systems Workshop, 2020

2019

Merlin: Enabling Machine Learning-Ready HPC Ensembles.

J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom

CoRR, 2019

Comparing GPU Power and Frequency Capping: A Case Study with the MuMMI Workflow.

Tapasya Patki, Zachary Frye, Harsh Bhatia, Francesco Di Natale, James N. Glosli, Helgi I. Ingólfsson, Barry Rountree

Proceedings of the 2019 IEEE/ACM Workflows in Support of Large-Scale Science, 2019

A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer.

Francesco Di Natale, Harsh Bhatia, Timothy S. Carpenter, Chris Neale, Sara Kokkila Schumacher, Tomas Oppelstrup, Liam Stanton, Xiaohua Zhang, Shiv Sundram, Thomas R. W. Scogland, Gautham Dharuman, Michael P. Surh, Yue Yang, Claudia Misale, Lars Schneidenbach, Carlos H. A. Costa, Changhoan Kim, Bruce D'Amora, Sandrasegaram Gnanakaran, Dwight V. Nissley, Frederick H. Streitz, Felice C. Lightstone, Peer-Timo Bremer, James N. Glosli, Helgi I. Ingólfsson

Proceedings of the International Conference for High Performance Computing, 2019