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Deep Learning Recommendation Model for Personalization and Recommendation Systems

M. Naumov, D. Mudigere, H. Shi, J. Huang, N. Sundaraman, J. Park, X. Wang, U. Gupta, C. Wu, A. Azzolini, D. Dzhulgakov, A. Mallevich, I. Cherniavskii, Y. Lu, R. Krishnamoorthi, A. Yu, V. Kondratenko, S. Pereira, X. Chen, W. Chen, V. Rao, B. Jia, L. Xiong, and M. Smelyanskiy. (2019)cite arxiv:1906.00091Comment: 10 pages, 6 figures.

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Rosemary Park

Jinhyung Park

Kwan Park

Shinja Park

June Park

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Dynamic fine-grained sparse memory accesses.B. Akin, C. Chou, J. Park, C. Hughes, and R. Agarwal. MEMSYS, page 85-97. ACM, (2018)Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications.J. Park, M. Naumov, P. Basu, S. Deng, A. Kalaiah, D. Khudia, J. Law, P. Malani, A. Malevich, N. Satish and 18 other author(s). CoRR, (2018)With 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 and 12 other author(s). ISCA, page 83:1-83:13. ACM, (2023)Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization.C. Unger, Z. Jia, W. Wu, S. Lin, M. Baines, C. Narvaez, V. Ramakrishnaiah, N. Prajapati, P. McCormick, J. Mohd-Yusof and 5 other author(s). OSDI, page 267-284. USENIX Association, (2022)A framework for low-communication 1-D FFT.P. Tang, J. Park, D. Kim, and V. Petrov. Sci. Program., 21 (3-4): 181-195 (2013)High-performance algebraic multigrid solver optimized for multi-core based distributed parallel systems.J. Park, M. Smelyanskiy, U. Yang, D. Mudigere, and P. Dubey. SC, page 54:1-54:12. ACM, (2015)Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters.K. Vaidyanathan, K. Pamnany, D. Kalamkar, A. Heinecke, M. Smelyanskiy, J. Park, D. Kim, A. Shet, B. Kaul, B. Joó and 1 other author(s). IPDPS, page 1083-1092. IEEE Computer Society, (2014)Location-aware cache management for many-core processors with deep cache hierarchy.J. Park, R. Yoo, D. Khudia, C. Hughes, and D. Kim. SC, page 20:1-20:12. ACM, (2013)Enabling Sparse Winograd Convolution by Native Pruning.S. Li, J. Park, and P. Tang. CoRR, (2017)Gate scheduling for quantum algorithms.G. Guerreschi, and J. Park. CoRR, (2017)

BibSonomy

Disambiguation of "Park, Jongsoo"

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Deep Learning Recommendation Model for Personalization and Recommendation Systems

Please choose a person to relate this publication to

Rosemary Park

Jinhyung Park

Kwan Park

Shinja Park

June Park

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Park, Jongsoo"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep Learning Recommendation Model for Personalization and Recommendation Systems

Please choose a person to relate this publication to

Rosemary Park

Jinhyung Park

Kwan Park

Shinja Park

June Park

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
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URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Deep Learning Recommendation Model for Personalization and Recommendation Systems