Deep NLP-Based Co-Evolvement for Synthesizing Code Analysis from Natural Language
Zifan Nan, Hui Guan, Xipeng Shen, and Chunhua Liao
In The ACM SIGPLAN 2021 International Conference on Compiler Construction (CC 2021)
Publications
An Automatic Synthesizer of Advising Tools for High Performance Computing
Hui Guan, Xipeng Shen, and Hamid Krim
In IEEE Transactions on Parallel and Distributed Systems (TPDS)
HISyn: Human Learning-Inspired Natural Language Programming
Zifan Nan, Hui Guan, Xipeng Shen
In The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Sacramento, California, United States, November 2020. (acceptance rate: 101/360=28%)
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks
Hui Guan, Laxmikant Kishor Mokadam, Xipeng Shen, Seung-Hwan Lim, Robert Patton
In 3rd Conference on Machine Learning and Systems (MLSys), March 2020, Austin, TX, USA. (Acceptance rate: 20% (34/170))
In-Place Zero-Space Memory Protection for CNN
Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, and Seung-Hwan Lim
In Advances in Neural Information Processing Systems (NeurIPS), 2019. (Acceptance rate: 21.2% (1428/6743))
Post-Training 4-bit Quantization on Embedding Tables
Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen
In MLSys Workshop on Systems for ML @ NeurIPS, 2019 (Poster)
Wootz: a Compiler-Based Framework for Fast CNN Pruning via Composability
Hui Guan, Xipeng Shen, and Seung-Hwan Lim
In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019. (Acceptance rate: 27.7% (76/274))
Adaptive Deep Reuse: Accelerating CNN Training on the Fly
Lin Ning, Hui Guan, and Xipeng Shen
In 35th International Conference on Data Engineering (ICDE), 2019. (Acceptance rate: 18%)
Exploring Flexible Communications for Streamlining DNN Ensemble Training Pipelines
Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, and Robert M. Patton
In Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2018. (Acceptance rate: 23%)
Reuse-Centric K-Means Configuration
Hui Guan, Yufei Ding, Xipeng Shen, and Hamid Krim
In 34th International Conference on Data Engineering (ICDE), 2018. (short paper) (Acceptance rate: 23%)
TOP: A Compiler-Based Framework for Optimizing Machine Learning Algorithms through Generalized Triangle Inequality
Yufei Ding, Lin Ning, Hui Guan, Xipeng Shen, Madanlal Musuvathi, Todd Mytkowicz
In SysML, Feb 16th, 2018, Stanford University, 2018 (Poster)
Egeria: a Framework for Automatic Synthesis of HPC Advising Tools through Multi-Layered Natural Language Processing
Hui Guan, Xipeng Shen, and Hamid Krim
In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2017. (Acceptance rate: 18% (61/327))
Generalizations of the Theory and Deployment of Triangular Inequality for Compiler-Based Strength Reduction
Yufei Ding, Lin Ning, Hui Guan, Xipeng Shen
In Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2017. (Acceptance rate: 15% (47/322))
First Study on Data Readiness Level
Hui Guan, Thanos Gentimis, Hamid , and James Keiser
In arXiv preprint arXiv:1702.02107 (Preprint)
A Topological Collapse for Document Summarization
Hui Guan, Wen Tang, Hamid Krim, James Keiser, Andrew Rindos, and Radmila Sazdanovic
In IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2016.