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Alessandro Fanfarillo
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2020 – today
- 2023
- [c18]Nicholas Malaya
, Bronson Messer
Experiences readying applications for Exascale. SC 2023: 53:1-53:13 - [c17]Alessandro Fanfarillo
Efficient Probabilistic Tuning of Ensemble Forecasting Method. SC Workshops 2023: 384-386 - [i3]Paul T. Bauman, Reuben D. Budiardja, Dmytro Bykov, Noel Chalmers, Jacqueline Chen, Nicholas Curtis, Marc Day, Markus Eisenbach, Lucas Esclapez, Alessandro Fanfarillo, William Freitag, Nicholas Frontiere, Antigoni Georgiadou, Joseph Glenski, Kalyana C. Gottiparthi, Marc T. Henry de Frahan, Gustav R. Jansen, Wayne Joubert, Justin G. Lietz, Jakub Kurzak, Nicholas Malaya, Bronson Messer, Damon McDougall, Paul Mullowney, Stephen Nichols, Matthew R. Norman, Thomas Papatheodore, Jon S. Rood, Philip C. Roth, Sarat Sreepathi, James B. White III
Experiences Readying Applications for Exascale. CoRR abs/2310.01586 (2023) - 2021
- [j5]Alessandro Fanfarillo
Probabilistic forecasting using deep generative models. GeoInformatica 25(1): 127-147 (2021)
2010 – 2019
- 2019
- [j4]Alessandro Fanfarillo
Resilient computational applications using Coarray Fortran. Parallel Comput. 81: 58-67 (2019) - [c16]Sergio Rivas-Gomez, Alessandro Fanfarillo, Sébastien Valat, Christophe Laferriere, Philippe Couvée, Sai Narasimhamurthy, Stefano Markidis:
uMMAP-IO: User-Level Memory-Mapped I/O for HPC. HiPC 2019: 363-372 - [c15]Alessandro Fanfarillo, Davide Del Vento:
AITuning: Machine Learning-Based Tuning Tool for Run-Time Communication Libraries. PARCO 2019: 409-418 - [c14]Sergio Rivas-Gomez, Alessandro Fanfarillo
Persistent coarrays: integrating MPI storage windows in coarray fortran. EuroMPI 2019: 3:1-3:8 - [c13]Alessandro Fanfarillo:
Quantifying Uncertainty in Source Term Estimation with Tensorflow Probability. UrgentHPC@SC 2019: 1-6 - [c12]Davide Del Vento, Alessandro Fanfarillo
Traps, Pitfalls and Misconceptions of Machine Learning applied to Scientific Disciplines. PEARC 2019: 75:1-75:8 - [i2]Alessandro Fanfarillo, Davide Del Vento:
AITuning: Machine Learning-based Tuning Tool for Run-Time Communication Libraries. CoRR abs/1909.06301 (2019) - [i1]Alessandro Fanfarillo, Behrooz Roozitalab, Weiming Hu, Guido Cervone:
Probabilistic Forecasting using Deep Generative Models. CoRR abs/1909.11865 (2019) - 2018
- [j3]Alessandro Fanfarillo
Notified access in coarray-based hydrodynamics applications on many-core architectures: Design and performance. Parallel Comput. 75: 118-129 (2018) - 2017
- [j2]Valeria Cardellini
Coarray-based load balancing on heterogeneous and many-core architectures. Parallel Comput. 68: 45-58 (2017) - [j1]Salvatore Filippone
Sparse Matrix-Vector Multiplication on GPGPUs. ACM Trans. Math. Softw. 43(4): 30:1-30:49 (2017) - [c11]Alessandro Fanfarillo
Optimizing Communication and Synchronization in CAF Applications. PARCO 2017: 191-200 - [c10]Alessandro Fanfarillo
Notified access in coarray fortran. EuroMPI/USA 2017: 12:1-12:7 - [c9]Damian W. I. Rouson, Ethan D. Gutmann
Performance portability of an intermediate-complexity atmospheric research model in coarray Fortran. PAW@SC 2017: 4:1-4:4 - [c8]Damian W. I. Rouson, James L. McCreight, Alessandro Fanfarillo
Incremental caffeination of a terrestrial hydrological modeling framework using Fortran 2018 teams. PAW@SC 2017: 6:1-6:4 - 2016
- [c7]Valeria Cardellini
Heterogeneous CAF-Based Load Balancing on Intel Xeon Phi. IPDPS Workshops 2016: 702-711 - [c6]Alessandro Fanfarillo
CAF Events Implementation Using MPI-3 Capabilities. EuroMPI 2016: 198-207 - 2015
- [c5]Valeria Cardellini
Hybrid Coarrays: a PGAS Feature for Many-Core Architectures. PARCO 2015: 175-184 - 2014
- [c4]Alessandro Fanfarillo
Coarrays in GNU Fortran. PACT 2014: 513-514 - [c3]Valeria Cardellini
Sparse matrix computations on clusters with GPGPUs. HPCS 2014: 23-30 - [c2]Alessandro Fanfarillo
OpenCoarrays: Open-source Transport Layers Supporting Coarray Fortran Compilers. PGAS 2014: 4:1-4:11 - 2013
- [c1]Valeria Cardellini
Heterogeneous Sparse Matrix Computations on Hybrid GPU/CPU Platforms. PARCO 2013: 203-212
Coauthor Index
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