| Deep learning at 15pf: supervised and semi-supervised classification for scientific data T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ... Proceedings of the International Conference for High Performance Computing …, 2017 | 95 | 2017 |
| Communication optimizations for distributed machine learning S Sridharan, K Vaidyanathan, D Das, C Sakthivel, ME Smorkalov US Patent 11,270,201, 2022 | 63 | 2022 |
| On scale-out deep learning training for cloud and hpc S Sridharan, K Vaidyanathan, D Kalamkar, D Das, ME Smorkalov, ... arXiv preprint arXiv:1801.08030, 2018 | 35 | 2018 |
| TensorFlow at Scale: Performance and productivity analysis of distributed training with Horovod, MLSL, and Cray PE ML T Kurth, M Smorkalov, P Mendygral, S Sridharan, A Mathuriya Concurrency and Computation: Practice and Experience 31 (16), e4989, 2019 | 23 | 2019 |
| Training google neural machine translation on an intel cpu cluster DD Kalamkar, K Banerjee, S Srinivasan, S Sridharan, E Georganas, ... 2019 IEEE International Conference on Cluster Computing (CLUSTER), 1-10, 2019 | 8 | 2019 |
| Prabhat, and P. Dubey,“Deep learning at 15PF: Supervised and semi-supervised classification for scientific data,” T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ... Proc. International Conference for High Performance Computing, Networking …, 2017 | 7 | 2017 |
| A General Neural-Networks-Based Method for Identification of Partial Differential Equations, Implemented on a Novel AI Accelerator MA Krinitskiy, VM Stepanenko, AO Malkhanov, ME Smorkalov Supercomputing Frontiers and Innovations 9 (3), 19-50, 2022 | 4 | 2022 |
| About optimal loss function for training physics-informed neural networks under respecting causality VA Es' kin, DV Davydov, ED Egorova, AO Malkhanov, MA Akhukov, ... arXiv preprint arXiv:2304.02282, 2023 | 3 | 2023 |
| TensorFlow at Scale-MPI, RDMA and All That T Kurth, M Smorkalov, P Mendygral, S Sridharan, A Mathuriya CUG'18, 2018 | 1 | 2018 |
| Separable Physics-Informed Neural Networks for the solution of elasticity problems VA Es' kin, DV Davydov, JV Gur'eva, AO Malkhanov, ME Smorkalov arXiv preprint arXiv:2401.13486, 2024 | | 2024 |
| Catenary and Mercator projection MA Akhukov, VA Es' kin, ME Smorkalov arXiv preprint arXiv:2401.12991, 2024 | | 2024 |
| Communication optimizations for distributed machine learning S Sridharan, K Vaidyanathan, D Das, C Sakthivel, ME Smorkalov US Patent App. 18/320,385, 2023 | | 2023 |
| Communication optimizations for distributed machine learning S Sridharan, K Vaidyanathan, D Das, C Sakthivel, ME Smorkalov US Patent 11,704,565, 2023 | | 2023 |
| Method and apparatus for improving accuracy of physics informed neural networks in single and mixed precision M Smorkalov, A Malkhanov, V Kocheganov, D Davydov WO Patent WO2023068952A1, 2023 | | 2023 |
| Initialization and management of class of service attributes in runtime to optimize deep learning training in distributed environments A Anantaraman, S Sridharan, A Durg, MR Haghighat, ME Smorkalov, ... US Patent 11,249,910, 2022 | | 2022 |
| Вероятностные методы в нахождении среднего значения квадрата определителя (0,1) - матриц, содержащих заданное число единиц М Сморкалов Статистика. Моделирование. Оптимизация: сборник трудов Всероссийской …, 2011 | | 2011 |
| Среднее значение квадрата определителя в классе (0,1)-матриц, содержащих заданное число единиц М Сморкалов Обозрение прикладной и промышленной математики 18 (3), 502-504, 2011 | | 2011 |
| Численное нахождение количественных характеристик некоторых {0, 1}-матриц ВН Шевченко, МЕ Сморкалов ПРОБЛЕМЫ ТЕОРЕТИЧЕСКОЙ КИБЕРНЕТИКИ, 556-560, 2011 | | 2011 |
| Применение разностных уравнений в задачах случайного блуждания ВА Зорин, МЕ Сморкалов, ВМ Сморкалова | | 2004 |
| Valeriu Codreanu, SURFsara, Netherlands Ian Foster, UChicago & ANL, USA Zhao Zhang, TACC, USA S Feng, ETH Torsten Hoefler, SJ Li, D Podareanu, Q Pu, J Qiu, V Saletore, ... | | |
