| Megatron-lm: Training multi-billion parameter language models using model parallelism M Shoeybi, M Patwary, R Puri, P LeGresley, J Casper, B Catanzaro arXiv preprint arXiv:1909.08053, 2019 | 1032 | 2019 |
| Deep voice: Real-time neural text-to-speech SÖ Arık, M Chrzanowski, A Coates, G Diamos, A Gibiansky, Y Kang, X Li, ... International conference on machine learning, 195-204, 2017 | 741 | 2017 |
| Bloom: A 176b-parameter open-access multilingual language model BS Workshop, TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, ... arXiv preprint arXiv:2211.05100, 2022 | 713 | 2022 |
| Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model S Smith, M Patwary, B Norick, P LeGresley, S Rajbhandari, J Casper, ... arXiv preprint arXiv:2201.11990, 2022 | 360 | 2022 |
| Efficient large-scale language model training on gpu clusters using megatron-lm D Narayanan, M Shoeybi, J Casper, P LeGresley, M Patwary, ... Proceedings of the International Conference for High Performance Computing …, 2021 | 289 | 2021 |
| On the use of the Ffowcs Williams-Hawkings equation to predict far-field jet noise from large-eddy simulations S Mendez, M Shoeybi, SK Lele, P Moin International Journal of Aeroacoustics 12 (1-2), 1-20, 2013 | 146 | 2013 |
| Training question answering models from synthetic data R Puri, R Spring, M Patwary, M Shoeybi, B Catanzaro arXiv preprint arXiv:2002.09599, 2020 | 116 | 2020 |
| MEGATRON-CNTRL: Controllable story generation with external knowledge using large-scale language models P Xu, M Patwary, M Shoeybi, R Puri, P Fung, A Anandkumar, B Catanzaro arXiv preprint arXiv:2010.00840, 2020 | 104 | 2020 |
| Stable and accurate schemes for the compressible Navier–Stokes equations K Mattsson, M Svärd, M Shoeybi Journal of Computational Physics 227 (4), 2293-2316, 2008 | 96 | 2008 |
| BioMegatron: Larger biomedical domain language model HC Shin, Y Zhang, E Bakhturina, R Puri, M Patwary, M Shoeybi, R Mani arXiv preprint arXiv:2010.06060, 2020 | 85 | 2020 |
| Long-short transformer: Efficient transformers for language and vision C Zhu, W Ping, C Xiao, M Shoeybi, T Goldstein, A Anandkumar, ... Advances in neural information processing systems 34, 17723-17736, 2021 | 82 | 2021 |
| Unsupervised video interpolation using cycle consistency FA Reda, D Sun, A Dundar, M Shoeybi, G Liu, KJ Shih, A Tao, J Kautz, ... Proceedings of the IEEE/CVF international conference on computer Vision, 892-900, 2019 | 81 | 2019 |
| End-to-end training of neural retrievers for open-domain question answering DS Sachan, M Patwary, M Shoeybi, N Kant, W Ping, WL Hamilton, ... arXiv preprint arXiv:2101.00408, 2021 | 70 | 2021 |
| Numerical investigation of the acoustic behavior of a multi-perforated liner J Eldredge, D Bodony, M Shoeybi 13th AIAA/CEAS Aeroacoustics Conference (28th AIAA Aeroacoustics Conference …, 2007 | 50 | 2007 |
| Factuality enhanced language models for open-ended text generation N Lee, W Ping, P Xu, M Patwary, PN Fung, M Shoeybi, B Catanzaro Advances in Neural Information Processing Systems 35, 34586-34599, 2022 | 49 | 2022 |
| An adaptive implicit–explicit scheme for the DNS and LES of compressible flows on unstructured grids M Shoeybi, M Svärd, FE Ham, P Moin Journal of Computational Physics 229 (17), 5944-5965, 2010 | 49 | 2010 |
| Large-eddy simulations of perfectly expanded supersonic jets using an unstructured solver S Mendez, M Shoeybi, A Sharma, FE Ham, SK Lele, P Moin AIAA journal 50 (5), 1103-1118, 2012 | 48 | 2012 |
| FP8 formats for deep learning P Micikevicius, D Stosic, N Burgess, M Cornea, P Dubey, R Grisenthwaite, ... arXiv preprint arXiv:2209.05433, 2022 | 47 | 2022 |
| Large-eddy simulations of perfectly-expanded supersonic jets: Quality assessment and validation S Mendez, M Shoeybi, A Sharma, F Ham, S Lele, P Moin 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and …, 2010 | 44 | 2010 |
| Reducing activation recomputation in large transformer models VA Korthikanti, J Casper, S Lym, L McAfee, M Andersch, M Shoeybi, ... Proceedings of Machine Learning and Systems 5, 2023 | 43 | 2023 |
