Dehao Chen

According to our database, Dehao Chen authored at least 24 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Quaternion Extreme Learning Machine Based on Real Augmented Representation.

Huisheng Zhang, Zaiqiang Wang, Dehao Chen, Shuai Zhu, Dongpo Xu

IEEE Signal Process. Lett., 2023

Overlap Communication with Dependent Computation via Decomposition in Large Deep Learning Models.

Shibo Wang, Jinliang Wei, Amit Sabne, Andy Davis, Berkin Ilbeyi, Blake Hechtman, Dehao Chen, Karthik Srinivasa Murthy, Marcello Maggioni, Qiao Zhang, Sameer Kumar, Tongfei Guo, Yuanzhong Xu, Zongwei Zhou

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

LaMDA: Language Models for Dialog Applications.

Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le

CoRR, 2022

News Recommendation Model Based on Long-Term and Short-Term Interests.

Lei Ren, Dehao Chen, Zexin Miao, Huisheng Zhang

Proceedings of the 5th International Conference on Big Data Technologies, 2022

2021

GSPMD: General and Scalable Parallelization for ML Computation Graphs.

Yuanzhong Xu, HyoukJoong Lee, Dehao Chen, Blake A. Hechtman, Yanping Huang, Rahul Joshi, Maxim Krikun, Dmitry Lepikhin, Andy Ly, Marcello Maggioni, Ruoming Pang, Noam Shazeer, Shibo Wang, Tao Wang, Yonghui Wu, Zhifeng Chen

CoRR, 2021

Exploring the Limits of Concurrency in ML Training on Google TPUS.

Sameer Kumar, Yu Emma Wang, Cliff Young, James Bradbury, Naveen Kumar, Dehao Chen, Andy Swing

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Exploring the limits of Concurrency in ML Training on Google TPUs.

Sameer Kumar, James Bradbury, Cliff Young, Yu Emma Wang, Anselm Levskaya, Blake A. Hechtman, Dehao Chen, HyoukJoong Lee, Mehmet Deveci, Naveen Kumar, Pankaj Kanwar, Shibo Wang, Skye Wanderman-Milne, Steve Lacy, Tao Wang, Tayo Oguntebi, Yazhou Zu, Yuanzhong Xu, Andy Swing

CoRR, 2020

Automatic Cross-Replica Sharding of Weight Update in Data-Parallel Training.

Yuanzhong Xu, HyoukJoong Lee, Dehao Chen, Hongjun Choi, Blake A. Hechtman, Shibo Wang

CoRR, 2020

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

Proceedings of the Third Conference on Machine Learning and Systems, 2020

2019

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

CoRR, 2019

Scale MLPerf-0.6 models on Google TPU-v3 Pods.

Sameer Kumar, Victor Bitorff, Dehao Chen, Chiachen Chou, Blake A. Hechtman, HyoukJoong Lee, Naveen Kumar, Peter Mattson, Shibo Wang, Tao Wang, Yuanzhong Xu, Zongwei Zhou

CoRR, 2019

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling.

Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia Xu Chen, Ye Jia, Anjuli Kannan, Tara N. Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George F. Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel Bacchiani, Thomas B. Jablin, Robert Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon

CoRR, 2019

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Xu Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Yonghui Wu, Zhifeng Chen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Image Classification at Supercomputer Scale.

Chris Ying, Sameer Kumar, Dehao Chen, Tao Wang, Youlong Cheng

CoRR, 2018

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism.

Yanping Huang, Yonglong Cheng, Dehao Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Zhifeng Chen

CoRR, 2018

2016

AutoFDO: automatic feedback-directed optimization for warehouse-scale applications.

Dehao Chen, Xinliang David Li, Tipp Moseley

Proceedings of the 2016 International Symposium on Code Generation and Optimization, 2016

2014

Hardware Counted Profile-Guided Optimization.

Baptiste Wicht, Roberto A. Vitillo, Dehao Chen, David Levinthal

CoRR, 2014

2013

Taming Hardware Event Samples for Precise and Versatile Feedback Directed Optimizations.

Dehao Chen, Neil Vachharajani, Robert Hundt, Xinliang D. Li, Stéphane Eranian, Wenguang Chen, Weimin Zheng

IEEE Trans. Computers, 2013

2012

Providing Source Code Level Portability Between CPU and GPU with MapCG.

Chun-Tao Hong, Dehao Chen, Yubei Chen, Wen-Guang Chen, Wei-Min Zheng, Haibo Lin

J. Comput. Sci. Technol., 2012

CUDA-Zero: a framework for porting shared memory GPU applications to multi-GPUs.

Dehao Chen, Wenguang Chen, Weimin Zheng

Sci. China Inf. Sci., 2012

2010

Taming hardware event samples for FDO compilation.

Dehao Chen, Neil Vachharajani, Robert Hundt, Shih-wei Liao, Vinodha Ramasamy, Paul Yuan, Wenguang Chen, Weimin Zheng

Proceedings of the CGO 2010, 2010

MapCG: writing parallel program portable between CPU and GPU.

Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin

Proceedings of the 19th International Conference on Parallel Architectures and Compilation Techniques, 2010

2006

Tree partition based parallel frequent pattern mining on shared memory systems.

Dehao Chen, Chunrong Lai, Wei Hu, Wenguang Chen, Yimin Zhang, Weimin Zheng

Proceedings of the 20th International Parallel and Distributed Processing Symposium (IPDPS 2006), 2006