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Shared Microexponents: A Little Shifting Goes a Long Way.

B. Rouhani, R. Zhao, V. Elango, R. Shafipour, M. Hall, M. Mesmakhosroshahi, A. More, L. Melnick, M. Golub, G. Varatkar, L. Shao, G. Kolhe, D. Melts, J. Klar, R. L'Heureux, M. Perry, D. Burger, E. Chung, Z. Deng, S. Naghshineh, J. Park, and M. Naumov. CoRR, (2023)

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Alexey Naumov

Sergej Naumov

Petru Joan Maxim

Angela Maximini

Adel Maximos

Other publications of authors with the same name

Deep Learning Recommendation Model for Personalization and Recommendation SystemsM. Naumov, D. Mudigere, H. Shi, J. Huang, N. Sundaraman, J. Park, X. Wang, U. Gupta, C. Wu, A. Azzolini and 14 other author(s). (2019)cite arxiv:1906.00091Comment: 10 pages, 6 figures.High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.D. Mudigere, Y. Hao, J. Huang, A. Tulloch, S. Sridharan, X. Liu, M. Ozdal, J. Nie, J. Park, L. Luo and 41 other author(s). CoRR, (2021)Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale.Z. Deng, J. Park, P. Tang, H. Liu, J. Yang, H. Yuen, J. Huang, D. Khudia, X. Wei, E. Wen and 8 other author(s). CoRR, (2021)RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.L. Ke, U. Gupta, C. Wu, B. Cho, M. Hempstead, B. Reagen, X. Zhang, D. Brooks, V. Chandra, U. Diril and 11 other author(s). CoRR, (2019)Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation.L. Luo, B. Zhang, M. Tsang, Y. Ma, C. Chu, Y. Chen, S. Li, Y. Hao, Y. Zhao, G. Lakshminarayanan and 4 other author(s). CoRR, (2024)Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems.H. Shi, D. Mudigere, M. Naumov, and J. Yang. CoRR, (2019)Bandana: Using Non-volatile Memory for Storing Deep Learning Models.A. Eisenman, M. Naumov, D. Gardner, M. Smelyanskiy, S. Pupyrev, K. Hazelwood, A. Cidon, and S. Katti. CoRR, (2018)On the Dimensionality of Embeddings for Sparse Features and Data.M. Naumov. CoRR, (2019)Spatial-Winograd Pruning Enabling Sparse Winograd Convolution.J. Yu, J. Park, and M. Naumov. CoRR, (2019)A Block-Oriented, Parallel and Collective Approach to Sparse Indefinite Preconditioning on GPUs.D. Thuerck, M. Naumov, M. Garland, and M. Goesele. IA3@SC, page 1-10. IEEE, (2018)

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Disambiguation of "Naumov, Maxim"

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Shared Microexponents: A Little Shifting Goes a Long Way.

Please choose a person to relate this publication to

Alexey Naumov

Sergej Naumov

Petru Joan Maxim

Angela Maximini

Adel Maximos

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Naumov, Maxim"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Shared Microexponents: A Little Shifting Goes a Long Way.

Please choose a person to relate this publication to

Alexey Naumov

Sergej Naumov

Petru Joan Maxim

Angela Maximini

Adel Maximos

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
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Shared Microexponents: A Little Shifting Goes a Long Way.