Jiesong Liu

Jiesong Liu

Ph.D. Student at North Carolina State University

Publications

You can also find my articles on my Google Scholar profile.

Conference Papers

[ASPLOS’25] Generalizing Reuse Patterns for Efficient DNN on Microcontrollers

Jiesong Liu, Bin Ren, Xipeng Shen

Published in The 30th ACM International Conference on Architecture Support for Programming Languages and Operating Systems (ASPLOS), 2025

Proposed Generalized Reuse, a framework that expands computation reuse strategies in neural networks, yielding 1.03-2.2× inference speedups or 1-8% accuracy improvements across diverse architectures.

Recommended citation: Jiesong Liu, Brian Park, Xipeng Shen. (2025). "Generalizing Reuse Patterns for Efficient DNN on Microcontrollers." ASPLOS 2025
Paper

[VLDB’24] A Systematic Study on Early Stop Metrics in HPO and the Implications of Uncertainty

Jiawei Guan, Feng Zhang, Jiesong Liu, Xipeng Shen

Published in International Conference on Very Large Data Bases (VLDB), 2024

This paper systematically studies the impact of different early stop metrics in hyperparameter optimization.

Recommended citation: Jiawei Guan, Feng Zhang, Jiesong Liu, Xipeng Shen. (2024). "A Systematic Study on Early Stop Metrics in HPO and the Implications of Uncertainty." VLDB 2024.

[NeurIPS’24] UQ-guided Hyperparameter Optimization for Iterative Learners

Jiesong Liu, Feng Zhang, Jiawei Guan, Xipeng Shen

Published in Conference on Neural Information Processing Systems (NeurIPS), 2024

This work explores uncertainty-guided hyperparameter optimization for iterative learning models.

Recommended citation: Jiesong Liu, Feng Zhang, Jiawei Guan, Xipeng Shen. (2024). "UQ-guided Hyperparameter Optimization for Iterative Learners." NeurIPS 2024.
Paper | Slides

[VLDB’23] Approximating Probabilistic Group Steiner Trees in Graphs

Shuang Yang, Yahui Sun, Jiesong Liu, Xiaokui Xiao, Ronghua Li, Zhewei Wei

Published in Proceedings of the VLDB Endowment (PVLDB), 2023

This paper presents a new approach to approximating probabilistic group Steiner trees in large-scale graphs.

Recommended citation: Shuang Yang, Yahui Sun, Jiesong Liu, Xiaokui Xiao, Ronghua Li, Zhewei Wei. (2023). "Approximating Probabilistic Group Steiner Trees in Graphs." VLDB 2023.
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[ASPLOS’23] Space Efficient TREC for Enabling Deep Learning on Microcontrollers

Jiesong Liu, Feng Zhang, Jiawei Guan, Hsing-Hsuan Sung, Xiaoyong Du, Xipeng Shen

Published in The ACM International Conference on Architecture Support for Programming Languages and Operating Systems (ASPLOS), 2023

This paper presents a space-efficient approach to transient redundancy elimination for deep learning on MCUs.

Recommended citation: Jiesong Liu, Feng Zhang, Jiawei Guan, Hsing-Hsuan Sung, Xiaoyong Du, Xipeng Shen. (2023). "Space Efficient TREC for Enabling Deep Learning on Microcontrollers." ASPLOS 2023.
Paper | Slides

[NeurIPS’22] TREC: Transient Redundancy Elimination-based Convolution

Jiawei Guan, Feng Zhang, Jiesong Liu, Hsing-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen

Published in Conference on Neural Information Processing Systems (NeurIPS), 2022

We propose TREC, a method that significantly reduces transient redundancy in convolutional computations.

Recommended citation: Jiawei Guan, Feng Zhang, Jiesong Liu, Hsing-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen. (2022). "TREC: Transient Redundancy Elimination-based Convolution." NeurIPS 2022.
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Journal Articles

[TPDS’24] G-Learned Index: Enabling Efficient Learned Index on GPU

Jiesong Liu, Feng Zhang, Lv Lu, Xiaoyong Du, Guoliang Li, Dong Deng

Published in IEEE Transactions on Parallel and Distributed Systems (TPDS), 2024

This work explores the efficient implementation of learned indexes optimized for GPU architectures.

Recommended citation: Jiesong Liu, Feng Zhang, Lv Lu, Xiaoyong Du, Guoliang Li, Dong Deng. (2024). "G-Learned Index: Enabling Efficient Learned Index on GPU." TPDS 2024.
Paper

[TC’24] Enabling Efficient Deep Learning on MCU with Transient Redundancy Elimination

Jiesong Liu, Feng Zhang, Jiawei Guan, Hsing-Hsuan Sung, Xiaoyong Du, Xipeng Shen

Published in IEEE Transactions on Computers (TC), 2024

We introduce a method for eliminating transient redundancy to improve deep learning efficiency on microcontrollers.

Recommended citation: Jiesong Liu, Feng Zhang, Jiawei Guan, Hsing-Hsuan Sung, Xiaoyong Du, Xipeng Shen. (2024). "Enabling Efficient Deep Learning on MCU with Transient Redundancy Elimination." IEEE TC.
Paper

[TPDS’22] Exploring Query Processing on CPU-GPU Integrated Edge Device

Jiesong Liu, Feng Zhang, Hourun Li, Dalin Wang, Weitao Wan, Xiaokun Fang, Jidong Zhai, Xiaoyong Du

Published in IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022

This paper explores efficient query processing techniques on CPU-GPU integrated edge devices.

Recommended citation: Jiesong Liu, Feng Zhang, Hourun Li, Dalin Wang, Weitao Wan, Xiaokun Fang, Jidong Zhai, Xiaoyong Du. (2022). "Exploring Query Processing on CPU-GPU Integrated Edge Device." TPDS 2022.
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