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DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

S. Song, B. Kruft, M. Zhang, C. Li, S. Chen, C. Zhang, M. Tanaka, X. Wu, J. Rasley, A. Awan, C. Holmes, M. Cai, A. Ghanem, Z. Zhou, Y. He, P. Luferenko, D. Kumar, J. Weyn, R. Zhang, S. Klocek, V. Vragov, M. AlQuraishi, G. Ahdritz, C. Floristean, C. Negri, R. Kotamarthi, V. Vishwanath, A. Ramanathan, S. Foreman, K. Hippe, T. Arcomano, R. Maulik, M. Zvyagin, A. Brace, B. Zhang, C. Bohorquez, A. Clyde, B. Kale, D. Perez-Rivera, H. Ma, C. Mann, M. Irvin, J. Pauloski, L. Ward, V. Hayot-Sasson, M. Emani, Z. Xie, D. Lin, M. Shukla, I. Foster, J. Davis, M. Papka, T. Brettin, P. Balaprakash, G. Tourassi, J. Gounley, H. Hanson, T. Potok, M. Pasini, K. Evans, D. Lu, D. Lunga, J. Yin, S. Dash, F. Wang, M. Shankar, I. Lyngaas, X. Wang, G. Cong, P. Zhang, M. Fan, S. Liu, A. Hoisie, S. Yoo, Y. Ren, W. Tang, K. Felker, A. Svyatkovskiy, H. Liu, A. Aji, A. Dalton, M. Schulte, K. Schulz, Y. Deng, W. Nie, J. Romero, C. Dallago, A. Vahdat, C. Xiao, T. Gibbs, A. Anandkumar, and R. Stevens. CoRR, (2023)

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Li Li

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Better Caching in Search Advertising Systems with Rapid Refresh Predictions.C. Li, D. Andersen, Q. Fu, S. Elnikety, and Y. He. WWW, page 1875-1884. ACM, (2018)Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam.Y. Lu, C. Li, M. Zhang, C. Sa, and Y. He. CoRR, (2022)1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed.C. Li, A. Awan, H. Tang, S. Rajbhandari, and Y. He. CoRR, (2021)DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.S. Song, B. Kruft, M. Zhang, C. Li, S. Chen, C. Zhang, M. Tanaka, X. Wu, J. Rasley, A. Awan and 82 other author(s). CoRR, (2023)1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed.C. Li, A. Awan, H. Tang, S. Rajbhandari, and Y. He. HIPC, page 272-281. IEEE, (2022)The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models.C. Li, M. Zhang, and Y. He. NeurIPS, (2022)Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam.Y. Lu, C. Li, M. Zhang, C. Sa, and Y. He. ICLR, OpenReview.net, (2023)DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales.Z. Yao, R. Aminabadi, O. Ruwase, S. Rajbhandari, X. Wu, A. Awan, J. Rasley, M. Zhang, C. Li, C. Holmes and 9 other author(s). CoRR, (2023)Curriculum Learning: A Regularization Method for Efficient and Stable Billion-Scale GPT Model Pre-Training.C. Li, M. Zhang, and Y. He. CoRR, (2021)Extreme Compression for Pre-trained Transformers Made Simple and Efficient.X. Wu, Z. Yao, M. Zhang, C. Li, and Y. He. CoRR, (2022)

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Disambiguation of "Li, Conglong"

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DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

Please choose a person to relate this publication to

Li Li

Li Li

Li Li

Li Li

Li Li

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Li, Conglong"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

Please choose a person to relate this publication to

Li Li

Li Li

Li Li

Li Li

Li Li

Other publications of authors with the same name

Disambiguation

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DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.