Suyog Gupta
Suyog Gupta
Google, IBM T. J. Watson Research Center, Stanford University
Verified email at
Cited by
Cited by
Deep learning with limited numerical precision
S Gupta, A Agrawal, K Gopalakrishnan, P Narayanan
International Conference on Machine Learning, 1737-1746, 2015
Achieving direct band gap in germanium through integration of Sn alloying and external strain
S Gupta, B Magyari-Köpe, Y Nishi, KC Saraswat
Journal of Applied Physics 113 (7), 073707, 2013
To prune, or not to prune: exploring the efficacy of pruning for model compression
M Zhu, S Gupta
arXiv preprint arXiv:1710.01878, 2017
Staleness-aware Async-SGD for Distributed Deep Learning
W Zhang, S Gupta, X Lian, J Liu
arXiv preprint arXiv:1511.05950, 2015
GeSn technology: Extending the Ge electronics roadmap
S Gupta, R Chen, B Magyari-Kope, H Lin, B Yang, A Nainani, Y Nishi, ...
Electron Devices Meeting (IEDM), 2011 IEEE International, 16.6. 1-16.6. 4, 2011
Demonstration of a Ge/GeSn/Ge quantum-well microdisk resonator on silicon: enabling high-quality Ge (Sn) materials for micro-and nanophotonics
R Chen, S Gupta, YC Huang, Y Huo, CW Rudy, E Sanchez, Y Kim, ...
Nano letters 14 (1), 37-43, 2014
Material characterization of high Sn-content, compressively-strained GeSn epitaxial films after rapid thermal processing
R Chen, YC Huang, S Gupta, AC Lin, E Sanchez, Y Kim, KC Saraswat, ...
Journal of Crystal Growth 365, 29-34, 2013
Model accuracy and runtime tradeoff in distributed deep learning: A systematic study
S Gupta, W Zhang, F Wang
2016 IEEE 16th International Conference on Data Mining (ICDM), 171-180, 2016
Model accuracy and runtime tradeoff in distributed deep learning: A systematic study
S Gupta, W Zhang, F Wang
2016 IEEE 16th International Conference on Data Mining (ICDM), 171-180, 2016
7-nm FinFET CMOS Design Enabled by Stress Engineering Using Si, Ge, and Sn
S Gupta, V Moroz, L Smith, Q Lu, KC Saraswat
IEEE, 2014
Hole Mobility Enhancement in Compressively Strained Ge0. 93Sn0. 07 pMOSFETs
S Gupta, YC Huang, Y Kim, E Sanchez, KC Saraswat
Highly Selective Dry Etching of Germanium over Germanium–Tin (Ge1–x Sn x): A Novel Route for Ge1–x Sn x Nanostructure Fabrication
S Gupta, R Chen, YC Huang, Y Kim, E Sanchez, JS Harris, KC Saraswat
Nano letters 13 (8), 3783-3790, 2013
Theoretical analysis of GeSn alloys as a gain medium for a Si-compatible laser
B Dutt, H Lin, DS Sukhdeo, BM Vulovic, S Gupta, D Nam, KC Saraswat, ...
IEEE Journal of Selected Topics in Quantum Electronics 19 (5), 1502706-1502706, 2013
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ...
arXiv preprint arXiv:1902.08295, 2019
Approximate computing: Challenges and opportunities
A Agrawal, J Choi, K Gopalakrishnan, S Gupta, R Nair, J Oh, DA Prener, ...
2016 IEEE International Conference on Rebooting Computing (ICRC), 1-8, 2016
New materials for post-Si computing: Ge and GeSn devices
S Gupta, X Gong, R Zhang, YC Yeo, S Takagi, KC Saraswat
MRS Bulletin 39 (08), 678-686, 2014
Towards high mobility GeSn channel nMOSFETs: Improved surface passivation using novel ozone oxidation method
S Gupta, B Vincent, B Yang, D Lin, F Gencarelli, JYJ Lin, R Chen, ...
Electron Devices Meeting (IEDM), 2012 IEEE International, 16.2. 1-16.2. 4, 2012
GeSn channel nMOSFETs: Material potential and technological outlook
S Gupta, B Vincent, DHC Lin, M Gunji, A Firrincieli, F Gencarelli, ...
VLSI Technology (VLSIT), 2012 Symposium on, 95-96, 2012
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study
S Gupta, W Zhang, F Wang
arXiv preprint arXiv:1509.04210, 2015
GeSn channel n and p MOSFETs
S Gupta, R Chen, B Vincent, D Lin, B Magyari-Kope, M Caymax, ...
ECS Transactions 50 (9), 937, 2013
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