| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1130 | 2023 |
| ZeRO: Memory optimizations toward training trillion parameter models S Rajbhandari, J Rasley, O Ruwase, Y He SC20: International Conference for High Performance Computing, Networking …, 2020 | 759 | 2020 |
| Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters J Rasley, S Rajbhandari, O Ruwase, Y He Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 661 | 2020 |
| 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 | 487 | 2022 |
| {Zero-offload}: Democratizing {billion-scale} model training J Ren, S Rajbhandari, RY Aminabadi, O Ruwase, S Yang, M Zhang, D Li, ... 2021 USENIX Annual Technical Conference (USENIX ATC 21), 551-564, 2021 | 227 | 2021 |
| Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning S Rajbhandari, O Ruwase, J Rasley, S Smith, Y He Proceedings of the international conference for high performance computing …, 2021 | 202 | 2021 |
| Learning intrinsic sparse structures within long short-term memory W Wen, Y He, S Rajbhandari, M Zhang, W Wang, F Liu, B Hu, Y Chen, ... arXiv preprint arXiv:1709.05027, 2017 | 150 | 2017 |
| Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale S Rajbhandari, C Li, Z Yao, M Zhang, RY Aminabadi, AA Awan, J Rasley, ... International conference on machine learning, 18332-18346, 2022 | 140 | 2022 |
| Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale RY Aminabadi, S Rajbhandari, AA Awan, C Li, D Li, E Zheng, O Ruwase, ... SC22: International Conference for High Performance Computing, Networking …, 2022 | 121 | 2022 |
| Rewon Child, Reza Yazdani Aminabadi, Julie Bernauer, Xia Song, Mohammad Shoeybi, Yuxiong He, Michael Houston, Saurabh Tiwary, and Bryan Catanzaro S Smith, M Patwary, B Norick, P LeGresley, S Rajbhandari, J Casper, ... Using deepspeed and megatron to train megatron-turing nlg 530b, a large …, 2022 | 119 | 2022 |
| {DeepCPU}: Serving {RNN-based} Deep Learning Models 10x Faster M Zhang, S Rajbhandari, W Wang, Y He 2018 USENIX Annual Technical Conference (USENIX ATC 18), 951-965, 2018 | 114 | 2018 |
| 1-bit adam: Communication efficient large-scale training with adam’s convergence speed H Tang, S Gan, AA Awan, S Rajbhandari, C Li, X Lian, J Liu, C Zhang, ... International Conference on Machine Learning, 10118-10129, 2021 | 69 | 2021 |
| Scalable and efficient moe training for multitask multilingual models YJ Kim, AA Awan, A Muzio, AFC Salinas, L Lu, A Hendy, S Rajbhandari, ... arXiv preprint arXiv:2109.10465, 2021 | 58 | 2021 |
| Neural network training performance optimization framework TA Chilimbi, O Ruwase, S Rajbhandari, M Carbin, Y He US Patent App. 14/986,186, 2017 | 39 | 2017 |
| A communication-optimal framework for contracting distributed tensors S Rajbhandari, A Nikam, PW Lai, K Stock, S Krishnamoorthy, ... SC'14: Proceedings of the International Conference for High Performance …, 2014 | 35 | 2014 |
| Optimizing CNNs on multicores for scalability, performance and goodput S Rajbhandari, Y He, O Ruwase, M Carbin, T Chilimbi ACM SIGARCH Computer Architecture News 45 (1), 267-280, 2017 | 30 | 2017 |
| A framework for load balancing of tensor contraction expressions via dynamic task partitioning PW Lai, K Stock, S Rajbhandari, S Krishnamoorthy, P Sadayappan Proceedings of the International Conference on High Performance Computing …, 2013 | 29 | 2013 |
| On fusing recursive traversals of Kd trees S Rajbhandari, J Kim, S Krishnamoorthy, LN Pouchet, F Rastello, ... Proceedings of the 25th International Conference on Compiler Construction …, 2016 | 28 | 2016 |
| 1-bit LAMB: communication efficient large-scale large-batch training with LAMB’s convergence speed C Li, AA Awan, H Tang, S Rajbhandari, Y He 2022 IEEE 29th International Conference on High Performance Computing, Data …, 2022 | 26 | 2022 |
| Deepspeed-chat: Easy, fast and affordable rlhf training of chatgpt-like models at all scales Z Yao, RY Aminabadi, O Ruwase, S Rajbhandari, X Wu, AA Awan, ... arXiv preprint arXiv:2308.01320, 2023 | 25 | 2023 |
He YuxiongMicrosoft ResearchVerified email at microsoft.com
