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Scalable and Efficient MoE Training for Multitask Multilingual Models.

Y. Kim, A. Awan, A. Muzio, A. Cruz-Salinas, L. Lu, A. Hendy, S. Rajbhandari, Y. He, and H. Awadalla. CoRR, (2021)

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Shrija Rajbhandari

Sujan Rajbhandari

Meena Rajbhandari

Rajita Rajbhandari

Kishor Kumar Rajbhandari

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Fast LSTM Inference by Dynamic Decomposition on Cloud Systems.Y. You, Y. He, S. Rajbhandari, W. Wang, C. Hsieh, K. Keutzer, and J. Demmel. ICDM, page 748-757. IEEE, (2019)SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement.H. Qin, S. Rajbhandari, O. Ruwase, F. Yan, L. Yang, and Y. He. NeurIPS, page 20531-20544. (2021)Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis.S. Rajbhandari, F. Rastello, K. Kowalski, S. Krishnamoorthy, and P. Sadayappan. PPoPP, page 327-340. ACM, (2017)ZeRO-Offload: Democratizing Billion-Scale Model Training.J. Ren, S. Rajbhandari, R. Aminabadi, O. Ruwase, S. Yang, M. Zhang, D. Li, and Y. He. USENIX ATC, page 551-564. USENIX Association, (2021)Scalable and Efficient MoE Training for Multitask Multilingual Models.Y. Kim, A. Awan, A. Muzio, A. Cruz-Salinas, L. Lu, A. Hendy, S. Rajbhandari, Y. He, and H. Awadalla. CoRR, (2021)A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training.S. Singh, O. Ruwase, A. Awan, S. Rajbhandari, Y. He, and A. Bhatele. ICS, page 203-214. ACM, (2023)ZeRO-infinity: breaking the GPU memory wall for extreme scale deep learning.S. Rajbhandari, O. Ruwase, J. Rasley, S. Smith, and Y. He. SC, page 59. ACM, (2021)DeepSpeed- Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale.R. Aminabadi, S. Rajbhandari, A. Awan, C. Li, D. Li, E. Zheng, O. Ruwase, S. Smith, M. Zhang, J. Rasley and 1 other author(s). SC, page 46:1-46:15. IEEE, (2022)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, and H. Li. ICLR (Poster), OpenReview.net, (2018)DeepCPU: Serving RNN-based Deep Learning Models 10x Faster.M. Zhang, S. Rajbhandari, W. Wang, and Y. He. USENIX ATC, page 951-965. USENIX Association, (2018)

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Disambiguation of "Rajbhandari, Samyam"

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Scalable and Efficient MoE Training for Multitask Multilingual Models.

Please choose a person to relate this publication to

Shrija Rajbhandari

Sujan Rajbhandari

Meena Rajbhandari

Rajita Rajbhandari

Kishor Kumar Rajbhandari

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Rajbhandari, Samyam"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Scalable and Efficient MoE Training for Multitask Multilingual Models.

Please choose a person to relate this publication to

Shrija Rajbhandari

Sujan Rajbhandari

Meena Rajbhandari

Rajita Rajbhandari

Kishor Kumar Rajbhandari

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Scalable and Efficient MoE Training for Multitask Multilingual Models.