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Joshua Romero
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Journal Articles
- 2022
- [j6]Francesco Viola
, Vamsi Spandan, Valentina Meschini, Joshua Romero, Massimiliano Fatica, Marco D. de Tullio
, Roberto Verzicco
:
FSEI-GPU: GPU accelerated simulations of the fluid-structure-electrophysiology interaction in the left heart. Comput. Phys. Commun. 273: 108248 (2022) - 2020
- [j5]Joshua Romero
, Jacob Crabill
, Jerry Watkins
, Freddie D. Witherden, Antony Jameson:
ZEFR: A GPU-accelerated high-order solver for compressible viscous flows using the flux reconstruction method. Comput. Phys. Commun. 250: 107169 (2020) - [j4]Joshua Romero
, Mauro Bisson, Massimiliano Fatica, Massimo Bernaschi:
High performance implementations of the 2D Ising model on GPUs. Comput. Phys. Commun. 256: 107473 (2020) - 2018
- [j3]Xiaojue Zhu
, Everett H. Phillips, Vamsi Spandan, John Donners, Gregory Ruetsch, Joshua Romero, Rodolfo Ostilla Monico
, Yantao Yang, Detlef Lohse, Roberto Verzicco
, Massimiliano Fatica, Richard J. A. M. Stevens
:
AFiD-GPU: A versatile Navier-Stokes solver for wall-bounded turbulent flows on GPU clusters. Comput. Phys. Commun. 229: 199-210 (2018) - 2017
- [j2]Joshua Romero, Freddie D. Witherden, Antony Jameson:
A Direct Flux Reconstruction Scheme for Advection-Diffusion Problems on Triangular Grids. J. Sci. Comput. 73(2-3): 1115-1144 (2017) - 2016
- [j1]Joshua Romero, Kartikey Asthana, Antony Jameson:
A Simplified Formulation of the Flux Reconstruction Method. J. Sci. Comput. 67(1): 351-374 (2016)
Conference and Workshop Papers
- 2023
- [c8]Felix Liu, Vanitha Sankaranarayanan, Javier E. Villanueva-Meyer, Shawn Hervey-Jumper, James Hawkins, Pablo F. Damasceno, Mauro Bisson, Joshua Romero, Thorsten Kurth, Massimiliano Fatica, Eleftherios Garyfallidis, Ariel Rokem, Jason C. Crane, Sharmila Majumdar:
Clinical validation of rapid GPU-enabled DTI tractography of the brain. High Performance Computing for Imaging 2023: 1-4 - [c7]Aristeidis Tsaris
, Joshua Romero
, Thorsten Kurth
, Jacob D. Hinkle
, Hong-Jun Yoon
, Feiyi Wang
, Sajal Dash
, Georgia D. Tourassi
:
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - 2022
- [c6]Joshua Romero, Junqi Yin, Nouamane Laanait, Bing Xie, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson:
Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. NSDI 2022: 1027-1040 - [c5]Joshua Romero, Pedro Costa
, Massimiliano Fatica:
Distributed-memory simulations of turbulent flows on modern GPU systems using an adaptive pencil decomposition library. PASC 2022: 14:1-14:11 - 2019
- [c4]Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano
, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston:
Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. DLS@SC 2019: 1-11 - 2018
- [c3]Jesús Jaime Moreno Escobar
, Joshua Romero, Oswaldo Morales Matamoros
, Ricardo Tejeida Padilla:
CAR: Computerized Assistant Referee for Determining the Offside Rule in Soccer by Using Computer Vision. IntelliSys (2) 2018: 521-542 - [c2]Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston:
Exascale deep learning for climate analytics. SC 2018: 51:1-51:12 - 2017
- [c1]Joshua Romero, Everett H. Phillips, Gregory Ruetsch, Massimiliano Fatica, Filippo Spiga, Paolo Giannozzi:
A Performance Study of Quantum ESPRESSO's PWscf Code on Multi-core and GPU Systems. PMBS@SC 2017: 67-87
Informal and Other Publications
- 2019
- [i4]Joshua Romero, Mauro Bisson, Massimiliano Fatica, Massimo Bernaschi:
A Performance Study of the 2D Ising Model on GPUs. CoRR abs/1906.06297 (2019) - [i3]Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson:
Exascale Deep Learning for Scientific Inverse Problems. CoRR abs/1909.11150 (2019) - [i2]Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston, Prabhat, George E. Karniadakis:
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs. CoRR abs/1910.13444 (2019) - 2018
- [i1]Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston:
Exascale Deep Learning for Climate Analytics. CoRR abs/1810.01993 (2018)
Coauthor Index
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