Conferences

• [ICDM’21] Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. [PDF]
  Hui Guan, Umang Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, and Xipeng Shen.
  In IEEE International Conference on Data Mining, 2021 (short paper). (Acceptance rate: 20% (198/990))

• [ICS’21] NumaPerf: Predictive and Comprehensive NUMA Profiling. [PDF]
  Xin Zhao, Jin Zhou, Hui Guan, Wei Wang, Xu Liu, Tongping Liu.
  In Proceedings of International Conference on Supercomputing, 2021. (Acceptance rate: 25% (39/157))

• [CC’21] Deep NLP-Based Co-Evolvement for Synthesizing Code Analysis from Natural Language. [PDF]
  Zifan Nan, Hui Guan, Xipeng Shen, and Chunhua Liao.
  In The ACM SIGPLAN 2021 International Conference on Compiler Construction, 2021.

• [FSE’20] HISyn: Human Learning-Inspired Natural Language Programming. [PDF]
  Zifan Nan, Hui Guan, Xipeng Shen.
  In The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Sacramento, California, United States, November 2020. (Acceptance rate: 101/360=28%)

• [MLSys’20] FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. [PDF]
  Hui Guan, Laxmikant Kishor Mokadam, Xipeng Shen, Robert Patton.
  MLSys’20. (Acceptance rate: 20.0% (34/170)).

• [NeurIPS’19] In-Place Zero-Space Memory Protection for CNN. [PDF]
  Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, and Seung-Hwan Lim.
  In Advances in Neural Information Processing Systems, pp. 5735-5744. 2019. (Acceptance rate: 21.2% (1428/6743))

• [PLDI’19] Wootz: a Compiler-based Framework for Fast CNN Pruning via Composability. [PDF]
  Hui Guan, Xipeng Shen, and Seung-Hwan Lim.
  In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 717-730. ACM, 2019. (Acceptance rate: 27.7% (76/274))

• [ICDE’19] Adaptive Deep Reuse: Accelerating CNN Training on the Fly. [PDF]
  Lin Ning, Hui Guan, and Xipeng Shen.
  In 2019 IEEE 35th International Conference on Data Engineering (ICDE), pp. 1538-1549. IEEE, 2019. (Acceptance rate: 18%)

• [SC’18] Exploring Flexible Communications for Streamlining DNN Ensemble Training Pipelines. [PDF]
  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, p. 64. IEEE, 2018. (Acceptance rate: 23%)

• [ICDE’18] Reuse-Centric K-Means Configuration. [PDF]]
  Hui Guan, Yufei Ding, Xipeng Shen, and Hamid Krim.
  In 2018 IEEE 34th International Conference on Data Engineering (ICDE), pp. 1224-1227. IEEE, 2018. (short paper) (Acceptance rate: 23%)

• [SC’17] Egeria: a Framework for Automatic Synthesis of HPC Advising Tools through Multi-Layered Natural Language Processing. [PDF]
  Hui Guan, Xipeng Shen, and Hamid Krim.
  In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, p. 10. ACM, 2017. (Acceptance rate: 18% (61/327))

• [PLDI’17] “Generalizations of the Theory and Deployment of Triangular Inequality for Compiler-Based Strength Reduction. [PDF]
  Yufei Ding, Lin Ning, Hui Guan, and Xipeng Shen.
  In Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 33-48. ACM, 2017. (Acceptance rate: 15% (47/322))

Journals

• [OSR’21] Scalable Graph Neural Network Training: The Case for Sampling. [PDF]
  Marco Serafini, Hui Guan.
  In ACM SIGOPS Operating Systems Review, 2021.

• [CACM’21] CoCoPIE: Enabling Real-Time AI on Off-the-Shelf Mobile Devices via Compression-Compilation Co-Design. [PDF]
  Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu, Bin Ren, Xipeng Shen, Yanzhi Wang, Pu Zhao. (Authors in Alphabetical Order)
  In Communications of the ACM, 2021.

• [InformationSystems’21] Reuse-Centric K-Means Configuration. [PDF]]
  Lijun Zhang, Hui Guan, Yufei Ding, Xipeng Shen, Hamid Krim.
  Information Systems, 2021.

• [TPDS’20] An Automatic Synthesizer of Advising Tools for High Performance Computing. [PDF]
  Hui Guan, Xipeng Shen, and Hamid Krim.
  In IEEE Transactions on Parallel and Distributed Systems (TPDS), 2020

Workshop & Poster Papers

• [MCHPC’21] FreeLunch: Compression-based GPU Memory Management for Convolutional Neural Networks. [PDF]
  Shaurya Patel, Tongping Liu, Hui Guan.
  In MCHPC’21 Workshop.

• [MLSys@NeurIPS’19] Post-Training 4-bit Quantization on Embedding Tables. [PDF]
  Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, and Hector Yuen.
  MLSys Workshop on Systems for ML @ NeurIPS, 2019.

• [SysML’18] TOP: A Compiler-Based Framework for Optimizing Machine Learning Algorithms through Generalized Triangle Inequality. [PDF]
  Yufei Ding, Lin Ning, Hui Guan, Xipeng Shen, Madanlal Musuvathi, Todd Mytkowicz.
  SysML, Feb 16th, 2018, Stanford University, 2018.

• [SPAWC’16] A topological collapse for document summarization. [PDF]
  Hui Guan, Wen Tang, Hamid Krim, James Keiser, Andrew Rindos, and Radmila Sazdanovic. In 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1-5. IEEE, 2016. \end{rSection}

Preprints

• First Study on Data Readiness Level. [PDF]
  Hui Guan, Thanos Gentimis, Hamid Krim, and James Keiser.
  arXiv preprint, 2017.