| On the Opportunities and Risks of Foundation Models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 1898 | 2021 |
| BLOOM: A 176B-Parameter Open-Access Multilingual Language Model TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... arXiv preprint arXiv:2211.05100, 2022 | 700 | 2022 |
| PipeDream: Generalized Pipeline Parallelism for DNN Training D Narayanan, A Harlap, A Phanishayee, V Seshadri, NR Devanur, ... 27th ACM Symposium on Operating Systems Principles, 1-15, 2019 | 582 | 2019 |
| DAWNBench: An End-to-End Deep Learning Benchmark and Competition C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ... NeurIPS Workshop on Systems for Machine Learning, 2017 | 355 | 2017 |
| Holistic Evaluation of Language Models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022 | 306 | 2022 |
| MLPerf Training Benchmark P Mattson, C Cheng, C Coleman, G Diamos, P Micikevicius, D Patterson, ... Third Conference on Machine Learning and Systems, 2020 | 287 | 2020 |
| 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 | 286 | 2021 |
| PipeDream: Fast and Efficient Pipeline Parallel DNN Training A Harlap, D Narayanan, A Phanishayee, V Seshadri, N Devanur, ... arXiv preprint arXiv:1806.03377, 2018 | 210 | 2018 |
| MacroBase: Prioritizing Attention in Fast Data P Bailis, E Gan, S Madden, D Narayanan, K Rong, S Suri Proceedings of the 2017 ACM International Conference on Management of Data …, 2017 | 175 | 2017 |
| Weld: A Common Runtime for High Performance Data Analytics S Palkar, JJ Thomas, A Shanbhag, D Narayanan, H Pirk, M Schwarzkopf, ... Conference on Innovative Data Systems Research (CIDR), 2017 | 163 | 2017 |
| Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads D Narayanan, K Santhanam, F Kazhamiaka, A Phanishayee, M Zaharia 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 147 | 2020 |
| Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark C Coleman, D Kang, D Narayanan, L Nardi, T Zhao, J Zhang, P Bailis, ... ACM SIGOPS Operating Systems Review 53 (1), 14-25, 2019 | 121 | 2019 |
| Memory-Efficient Pipeline-Parallel DNN Training D Narayanan, A Phanishayee, K Shi, X Chen, M Zaharia International Conference on Machine Learning, 7937-7947, 2021 | 119 | 2021 |
| Evaluating End-to-End Optimization for Data Analytics Applications in Weld S Palkar, J Thomas, D Narayanan, P Thaker, R Palamuttam, P Negi, ... Proceedings of the VLDB Endowment 11 (9), 1002-1015, 2018 | 87 | 2018 |
| Accelerating Deep Learning Workloads through Efficient Multi-Model Execution D Narayanan, K Santhanam, A Phanishayee, M Zaharia NeurIPS Workshop on Systems for Machine Learning, 2018 | 51 | 2018 |
| Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP D Narayanan, F Kazhamiaka, F Abuzaid, P Kraft, A Agrawal, S Kandula, ... 28th ACM Symposium on Operating Systems Principles, 2021 | 32 | 2021 |
| Weld: Rethinking the Interface Between Data-Intensive Applications S Palkar, JJ Thomas, D Narayanan, A Shanbhag, R Palamuttam, H Pirk, ... arXiv preprint arXiv:1709.06416, 2017 | 29 | 2017 |
| Analysis and Exploitation of Dynamic Pricing in the Public Cloud for ML Training D Narayanan, K Santhanam, F Kazhamiaka, A Phanishayee, M Zaharia Workshop on Distributed Infrastructure, Systems, Programming and AI (DISPA), 2020 | 21 | 2020 |
| Piper: Multidimensional Planner for DNN Parallelization JM Tarnawski, D Narayanan, A Phanishayee Advances in Neural Information Processing Systems 34, 24829-24840, 2021 | 20 | 2021 |
| Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference P Kraft, D Kang, D Narayanan, S Palkar, P Bailis, M Zaharia Third Conference on Machine Learning and Systems, 2020 | 20 | 2020 |
Matei ZahariaUC Berkeley and DatabricksVerified email at berkeley.edu
