Gabriele Merlo

According to our database, Gabriele Merlo authored at least 7 papers between 2018 and 2022.

Collaborative distances:

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

2022

The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science.

Eric Suchyta, Scott Klasky, Norbert Podhorszki, Matthew Wolf, Abolaji D. Adesoji, Choong-Seock Chang, Jong Choi, Philip E. Davis, Julien Dominski, Stéphane Ethier, Ian T. Foster, Kai Germaschewski, Berk Geveci, Chris Harris, Kevin A. Huck, Qing Liu, Jeremy Logan, Kshitij Mehta, Gabriele Merlo, Shirley V. Moore, Todd S. Munson, Manish Parashar, David Pugmire, Mark S. Shephard, Cameron W. Smith, Pradeep Subedi, Lipeng Wan, Ruonan Wang, Shuangxi Zhang

Int. J. High Perform. Comput. Appl., 2022

A general framework for quantifying uncertainty at scale and its application to fusion research.

Ionut-Gabriel Farcas, Gabriele Merlo, Frank Jenko

CoRR, 2022

2020

GENE-3D: A global gyrokinetic turbulence code for stellarators.

Maurice Maurer, A. Bañón Navarro, Tilman Dannert, Marco Restelli, Florian Hindenlang, Tobias Görler, Daniel Told, Denis Jarema, Gabriele Merlo, Frank Jenko

J. Comput. Phys., 2020

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE.

Paul Crandall, Denis Jarema, Hauke Doerk, Q. Pan, Gabriele Merlo, Tobias Görler, A. Bañón Navarro, Daniel Told, Maurice Maurer, Frank Jenko

Comput. Phys. Commun., 2020

2019

Scalable Performance Awareness for In Situ Scientific Applications.

Matthew Wolf, Julien Dominski, Gabriele Merlo, Jong Choi, Greg Eisenhauer, Stéphane Ethier, Kevin A. Huck, Scott Klasky, Jeremy Logan, Allen D. Malony, Chad Wood

Proceedings of the 15th International Conference on eScience, 2019

2018

FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning.

Zhao Zhang, Lei Huang, Uri Manor, Linjing Fang, Gabriele Merlo, Craig Michoski, John Cazes, Niall Gaffney

CoRR, 2018

Coupling Exascale Multiphysics Applications: Methods and Lessons Learned.

Jong Youl Choi, Choong-Seock Chang, Julien Dominski, Scott Klasky, Gabriele Merlo, Eric Suchyta, Mark Ainsworth, Bryce Allen, Franck Cappello, Michael Churchill, Philip E. Davis, Sheng Di, Greg Eisenhauer, Stéphane Ethier, Ian T. Foster, Berk Geveci, Hanqi Guo, Kevin A. Huck, Frank Jenko, Mark Kim, James Kress, Seung-Hoe Ku, Qing Liu, Jeremy Logan, Allen D. Malony, Kshitij Mehta, Kenneth Moreland, Todd S. Munson, Manish Parashar, Tom Peterka, Norbert Podhorszki, Dave Pugmire, Ozan Tugluk, Ruonan Wang, Ben Whitney, Matthew Wolf, Chad Wood

Proceedings of the 14th IEEE International Conference on e-Science, 2018