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Ping Tak Peter Tang
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Publications
- 2022
- [c27]Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Shanker Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen:
Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models. IEEE Big Data 2022: 1556-1563 - [c26]Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee:
SecNDP: Secure Near-Data Processing with Untrusted Memory. HPCA 2022: 244-258 - 2021
- [j21]Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy:
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 41(5): 93-100 (2021) - [c25]Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney:
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. KDD 2021: 2928-2936 - [i15]Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Shanker Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen:
Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models. CoRR abs/2103.00130 (2021) - [i14]Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy:
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR abs/2105.12676 (2021) - [i13]Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee:
SecNDP: Secure Near-Data Processing with Untrusted Memory. IACR Cryptol. ePrint Arch. 2021: 1642 (2021) - 2020
- [c24]Young Joon Kwon, Danielle Toussie, Lea Azour, Jose Concepcion, Corey Eber, G. Anthony Reina, Ping Tak Peter Tang, Amish H. Doshi, Eric K. Oermann, Anthony B. Costa:
Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images. ML4H@NeurIPS 2020: 179-193 - [i12]Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney:
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. CoRR abs/2010.08899 (2020) - [i11]Jie Amy Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch:
Mixed-Precision Embedding Using a Cache. CoRR abs/2010.11305 (2020) - 2019
- [c23]Greg Henry, Ping Tak Peter Tang, Alexander Heinecke:
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. ARITH 2019: 69-76 - [i10]Greg Henry, Ping Tak Peter Tang, Alexander Heinecke:
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. CoRR abs/1904.06376 (2019) - 2018
- [c21]Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang:
A Progressive Batching L-BFGS Method for Machine Learning. ICML 2018: 619-628 - [i9]Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang:
A Progressive Batching L-BFGS Method for Machine Learning. CoRR abs/1802.05374 (2018) - 2017
- [c20]Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang:
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. ICLR 2017 - [c19]Jongsoo Park, Sheng R. Li, Wei Wen, Ping Tak Peter Tang, Hai Li, Yiran Chen, Pradeep Dubey:
Faster CNNs with Direct Sparse Convolutions and Guided Pruning. ICLR (Poster) 2017 - [i7]Sheng R. Li, Jongsoo Park, Ping Tak Peter Tang:
Enabling Sparse Winograd Convolution by Native Pruning. CoRR abs/1702.08597 (2017) - 2016
- [i5]Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang:
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. CoRR abs/1609.04836 (2016) - 2014
- [c17]David E. Shaw, J. P. Grossman, Joseph A. Bank, Brannon Batson, J. Adam Butts, Jack C. Chao, Martin M. Deneroff, Ron O. Dror, Amos Even, Christopher H. Fenton, Anthony Forte, Joseph Gagliardo, Gennette Gill, Brian Greskamp, C. Richard Ho, Douglas J. Ierardi, Lev Iserovich, Jeffrey Kuskin, Richard H. Larson, Timothy Layman, Li-Siang Lee, Adam K. Lerer, Chester Li, Daniel Killebrew, Kenneth M. Mackenzie, Shark Yeuk-Hai Mok, Mark A. Moraes, Rolf Mueller, Lawrence J. Nociolo, Jon L. Peticolas, Terry Quan, Daniel Ramot, John K. Salmon, Daniele Paolo Scarpazza, U. Ben Schafer, Naseer Siddique, Christopher W. Snyder, Jochen Spengler, Ping Tak Peter Tang, Michael Theobald, Horia Toma, Brian Towles, Benjamin Vitale, Stanley C. Wang, Cliff Young:
Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer. SC 2014: 41-53 - 2013
- [j15]Jongsoo Park, Ping Tak Peter Tang, Mikhail Smelyanskiy, Daehyun Kim, Thomas Benson:
Efficient backprojection-based synthetic aperture radar computation with many-core processors. Sci. Program. 21(3-4): 165-179 (2013) - [j14]Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov:
A framework for low-communication 1-D FFT. Sci. Program. 21(3-4): 181-195 (2013) - [c15]Jongsoo Park, Ganesh Bikshandi, Karthikeyan Vaidyanathan, Ping Tak Peter Tang, Pradeep Dubey, Daehyun Kim:
Tera-scale 1D FFT with low-communication algorithm and Intel® Xeon Phi™ coprocessors. SC 2013: 34:1-34:12 - 2012
- [c14]Jongsoo Park, Ping Tak Peter Tang, Mikhail Smelyanskiy, Daehyun Kim, Thomas Benson:
Efficient backprojection-based synthetic aperture radar computation with many-core processors. SC 2012: 28 - [c13]Ping Tak Peter Tang, Jongsoo Park, Daehyun Kim, Vladimir Petrov:
A framework for low-communication 1-D FFT. SC 2012: 42 - 2011
- [c12]J. Adam Butts, Ping Tak Peter Tang, Ron O. Dror, David E. Shaw:
Radix-8 Digit-by-Rounding: Achieving High-Performance Reciprocals, Square Roots, and Reciprocal Square Roots. IEEE Symposium on Computer Arithmetic 2011: 149-158 - [c11]Ping Tak Peter Tang, J. Adam Butts, Ron O. Dror, David E. Shaw:
Tight Certification Techniques for Digit-by-Rounding Algorithms with Application to a New 1/sqrt(x) Design. IEEE Symposium on Computer Arithmetic 2011: 159-168 - 2009
- [j13]Marius Cornea, John Harrison, Cristina Anderson, Ping Tak Peter Tang, Eric Schneider, Evgeny Gvozdev:
A Software Implementation of the IEEE 754R Decimal Floating-Point Arithmetic Using the Binary Encoding Format. IEEE Trans. Computers 58(2): 148-162 (2009) - 2007
- [c10]Marius Cornea, Cristina Anderson, John Harrison, Ping Tak Peter Tang, Eric Schneider, Charles Tsen:
A Software Implementation of the IEEE 754R Decimal Floating-Point Arithmetic Using the Binary Encoding Format. IEEE Symposium on Computer Arithmetic 2007: 29-37 - 2003
- [c7]Marius Cornea, John Harrison, Ping Tak Peter Tang:
Intel® Itanium® floating-point architecture. WCAE 2003: 3 - 2002
- [j11]Bruce Greer, John Harrison, Greg Henry, Wei Wayne Li, Ping Tak Peter Tang:
Scientific computing on the Itanium® processor. Sci. Program. 10(4): 329-337 (2002) - 2001
- [c6]Bruce Greer, John Harrison, Greg Henry, Wei Wayne Li, Ping Tak Peter Tang:
Scientific computing on the Itanium processor. SC 2001: 41
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