| Differentiating between cancer and normal tissue samples using multi-hit combinations of genetic mutations S Dash, NA Kinney, RT Varghese, HR Garner, W Feng, ... Scientific reports 9 (1), 1005, 2019 | 30 | 2019 |
| Strategies to deploy and scale deep learning on the summit supercomputer J Yin, S Gahlot, N Laanait, K Maheshwari, J Morrison, S Dash, M Shankar 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), 84-94, 2019 | 20 | 2019 |
| Evaluation of pre-training large language models on leadership-class supercomputers J Yin, S Dash, J Gounley, F Wang, G Tourassi The Journal of Supercomputing 79 (18), 20747-20768, 2023 | 16 | 2023 |
| Identifying multi-hit carcinogenic gene combinations: Scaling up a weighted set cover algorithm using compressed binary matrix representation on a GPU Q Al Hajri, S Dash, W Feng, HR Garner, R Anandakrishnan Scientific reports 10 (1), 2022, 2020 | 15 | 2020 |
| Hvac: Removing i/o bottleneck for large-scale deep learning applications A Khan, AK Paul, C Zimmer, S Oral, S Dash, S Atchley, F Wang 2022 IEEE International Conference on Cluster Computing (CLUSTER), 324-335, 2022 | 13 | 2022 |
| Comparative evaluation of deep learning workloads for leadership-class systems J Yin, A Tsaris, S Dash, R Miller, F Wang, MA Shankar BenchCouncil Transactions on Benchmarks, Standards and Evaluations 1 (1), 100005, 2021 | 12 | 2021 |
| Image transformers for classifying acute lymphoblastic leukemia P Cho, S Dash, A Tsaris, HJ Yoon Medical Imaging 2022: Computer-Aided Diagnosis 12033, 647-653, 2022 | 10 | 2022 |
| Forge: Pre-training open foundation models for science J Yin, S Dash, F Wang, M Shankar Proceedings of the International Conference for High Performance Computing …, 2023 | 9 | 2023 |
| Optimizing distributed training on frontier for large language models S Dash, IR Lyngaas, J Yin, X Wang, R Egele, JA Ellis, M Maiterth, G Cong, ... ISC High Performance 2024 Research Paper Proceedings (39th International …, 2024 | 8 | 2024 |
| Strategies to deploy and scale deep learning on the summit supercomputer. In 2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS) J Yin, S Gahlot, N Laanait, K Maheshwari, J Morrison, S Dash, M Shankar IEEE, Denver, 84-94, 2019 | 8 | 2019 |
| iBLAST: Incremental BLAST of new sequences via automated e-value correction S Dash, SR Rahman, HM Hines, WC Feng PloS one 16 (4), e0249410, 2021 | 7* | 2021 |
| Portable parallel design of weighted multi-dimensional scaling for real-time data analysis S Dash, A Verma, C North, W Feng 2017 IEEE 19th International Conference on High Performance Computing and …, 2017 | 7 | 2017 |
| A scalable pipeline for gigapixel whole slide imaging analysis on leadership class hpc systems S Dash, B Hernández, A Tsaris, FT Alamudun, HJ Yoon, F Wang 2022 IEEE International Parallel and Distributed Processing Symposium …, 2022 | 6 | 2022 |
| Mitigating catastrophic forgetting in deep learning in a streaming setting using historical summary S Dash, J Yin, M Shankar, F Wang, W Feng 2021 7th International Workshop on Data Analysis and Reduction for Big …, 2021 | 6 | 2021 |
| DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies SL Song, B Kruft, M Zhang, C Li, S Chen, C Zhang, M Tanaka, X Wu, ... arXiv preprint arXiv:2310.04610, 2023 | 5 | 2023 |
| Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks A Tsaris, J Romero, T Kurth, J Hinkle, HJ Yoon, F Wang, S Dash, ... Proceedings of the Platform for Advanced Scientific Computing Conference, 1-11, 2023 | 3 | 2023 |
| Toward an Autonomous Workflow for Single Crystal Neutron Diffraction J Yin, G Zhang, H Cao, S Dash, BC Chakoumakos, F Wang Smoky Mountains Computational Sciences and Engineering Conference, 244-256, 2022 | 3 | 2022 |
| Ultra-Long Sequence Distributed Transformer X Wang, I Lyngaas, A Tsaris, P Chen, S Dash, MC Shekar, T Luo, ... arXiv preprint arXiv:2311.02382, 2023 | 2 | 2023 |
| BiGPICC: a graph-based approach to identifying carcinogenic gene combinations from mutation data V Oles, S Dash, R Anandakrishnan bioRxiv, 2023.02. 06.527327, 2023 | 2 | 2023 |
| Scaling out a combinatorial algorithm for discovering carcinogenic gene combinations to thousands of gpus S Dash, Q Al-Hajri, W Feng, HR Garner, R Anandakrishnan 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 2 | 2021 |
Feiyi WangDistinguished Research Scientist & Group Leader, Analytics and AI Methods at Scale, NCCS/ORNL在 ornl.gov 的电子邮件经过验证
