Narayanan, Deepak

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 2,676

Efficient large-scale language model training on GPU clusters using megatron-LM

Narayanan, D., Shoeybi, M., Casper, J., LeGresley, P., Patwary, M., Korthikanti, V., Vainbrand, D., Kashinkunti, P., Bernauer, J., Catanzaro, B., et al. (2021) · Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Parallel Computing and Optimization TechniquesTopic Modeling

Cited by 639

Holistic Evaluation of Language Models

Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 255

MLPerf Training Benchmark

Mattson, P., Cheng, C., Coleman, C., Diamos, G., Micikevicius, P., Patterson, D., Tang, H., Wei, G.-Y., Bailis, P., Bittorf, V., et al. (2019) · arXiv

Parallel Computing and Optimization TechniquesCloud Computing and Resource Management

Cited by 206

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Harlap, A., Narayanan, D., Phanishayee, A., Seshadri, V., Devanur, N., Ganger, G., & Gibbons, P. (2018) · arXiv

Parallel Computing and Optimization TechniquesStochastic Gradient Optimization Techniques

Cited by 153

Nemotron-4 340B Technical Report

Nvidia, :, Adler, B., Agarwal, N., Aithal, A., Anh, D. H., Bhattacharya, P., Brundyn, A., Casper, J., Catanzaro, B., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 66

An Empirical Study of Mamba-based Language Models

Waleffe, R., Byeon, W., Riach, D., Norick, B., Korthikanti, V., Dao, T., Gu, A., Hatamizadeh, A., Singh, S., Narayanan, D., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

Nemotron-4 15B Technical Report

Parmar, J., Prabhumoye, S., Jennings, J., Patwary, M., Subramanian, S., Su, D., Zhu, C., Narayanan, D., Jhunjhunwala, A., Dattagupta, A., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

Llama-Nemotron: Efficient Reasoning Models

Bercovich, A., Levy, I., Golan, I., Dabbah, M., El-Yaniv, R., Puny, O., Galil, I., Moshe, Z., Ronen, T., Nabwani, N., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

NVIDIA, :, Blakeman, A., Basant, A., Khattar, A., Renduchintala, A., Bercovich, A., Ficek, A., Bjorlin, A., Taghibakhshi, A., et al. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0