| Exascale deep learning for climate analytics T Kurth, S Treichler, J Romero, M Mudigonda, N Luehr, E Phillips, ... SC18: International conference for high performance computing, networking …, 2018 | 315 | 2018 |
| AFiD-GPU: a versatile Navier–Stokes solver for wall-bounded turbulent flows on GPU clusters X Zhu, E Phillips, V Spandan, J Donners, G Ruetsch, J Romero, ... Computer physics communications 229, 199-210, 2018 | 90 | 2018 |
| One-point statistics for turbulent pipe flow up to S Pirozzoli, J Romero, M Fatica, R Verzicco, P Orlandi Journal of fluid mechanics 926, A28, 2021 | 83 | 2021 |
| # COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol A Dommer, L Casalino, F Kearns, M Rosenfeld, N Wauer, SH Ahn, ... The international journal of high performance computing applications 37 (1 …, 2023 | 64 | 2023 |
| Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs L Yang, S Treichler, T Kurth, K Fischer, D Barajas-Solano, J Romero, ... 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), 1-11, 2019 | 53 | 2019 |
| GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics M Zvyagin, A Brace, K Hippe, Y Deng, B Zhang, CO Bohorquez, A Clyde, ... The International Journal of High Performance Computing Applications 37 (6 …, 2023 | 49 | 2023 |
| A simplified formulation of the flux reconstruction method J Romero, K Asthana, A Jameson Journal of Scientific Computing 67, 351-374, 2016 | 46 | 2016 |
| Exascale deep learning for scientific inverse problems N Laanait, J Romero, J Yin, MT Young, S Treichler, V Starchenko, ... arXiv preprint arXiv:1909.11150, 2019 | 33 | 2019 |
| ZEFR: A GPU-accelerated high-order solver for compressible viscous flows using the flux reconstruction method J Romero, J Crabill, JE Watkins, FD Witherden, A Jameson Computer Physics Communications 250, 107169, 2020 | 31 | 2020 |
| FSEI-GPU: GPU accelerated simulations of the fluid–structure–electrophysiology interaction in the left heart F Viola, V Spandan, V Meschini, J Romero, M Fatica, MD de Tullio, ... Computer physics communications 273, 108248, 2022 | 29 | 2022 |
| High performance implementations of the 2D Ising model on GPUs J Romero, M Bisson, M Fatica, M Bernaschi Computer Physics Communications 256, 107473, 2020 | 28 | 2020 |
| Verification and validation of HiFiLES: A high-order LES unstructured solver on multi-GPU platforms M Lopez-Morales, J Bull, J Crabill, TD Economon, D Manosalvas, ... 32nd AIAA applied aerodynamics conference, Atlanta, Georgia, USA, 16-20, 2014 | 26 | 2014 |
| Verification and Validation of HiFiLES: a High-Order LES unstructured solver on multi-GPU platforms MR López, A Sheshadri, JR Bull, TD Economon, J Romero, JE Watkins, ... 32nd AIAA applied aerodynamics conference, 3168, 2014 | 25 | 2014 |
| DNS of passive scalars in turbulent pipe flow S Pirozzoli, J Romero, M Fatica, R Verzicco, P Orlandi Journal of Fluid Mechanics 940, A45, 2022 | 24 | 2022 |
| A performance study of Quantum ESPRESSO’s PWscf code on multi-core and GPU systems J Romero, E Phillips, G Ruetsch, M Fatica, F Spiga, P Giannozzi High Performance Computing Systems. Performance Modeling, Benchmarking, and …, 2018 | 23 | 2018 |
| Multi-GPU, implicit time stepping for high-order methods on unstructured grids JE Watkins, J Romero, A Jameson 46th AIAA Fluid Dynamics Conference, 3965, 2016 | 20 | 2016 |
| A direct flux reconstruction scheme for advection–diffusion problems on triangular grids J Romero, FD Witherden, A Jameson Journal of Scientific Computing 73, 1115-1144, 2017 | 14 | 2017 |
| Extension of the flux reconstruction method to triangular elements using collapsed-edge quadrilaterals J Romero, A Jameson 54th AIAA Aerospace Sciences Meeting, 1825, 2016 | 12 | 2016 |
| Accelerating collective communication in data parallel training across deep learning frameworks J Romero, J Yin, N Laanait, B Xie, MT Young, S Treichler, V Starchenko, ... 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2022 | 11 | 2022 |
| Prabhat, and M T Kurth, S Treichler, J Romero, M Mudigonda, N Luehr, E Phillips, ... Houston,“Exascale Deep Learning for Climate Analytics,” in Proceedings of …, 2018 | 10 | 2018 |
