Hong-Xuan Wei, Pangfeng Liu, Ding-Yong Hong, Jan-Jan Wu, An-Tai Chen, "CNN Models Acceleration Using Filter Pruning and Sparse Tensor Core," International Journal on Networking and Computing, volume 12, number 2, pages 270-294, July 2022.
4.
Horng-Ruey Huang, Ding-Yong Hong, Jan-Jan Wu, Kung-Fu Chen, Pangfeng Liu, and Wei-Chung Hsu, "Accelerating Video Captioning on Heterogeneous System Architectures," ACM Transactions on Architecture and Code Optimization (TACO), volume 19, number 3, pages 1-25, May 2022.
Chun-Chen Hsu, Ding-Yong Hong, Wei-Chung Hsu, Pangfeng Liu and Jan-Jan Wu, "A Dynamic Binary Translation System in a Client/Server Environment," Journal of Systems Architecture (JSA), volume 61, number 7, pages 307 - 319, August 2015. :::
13.
Ding-Yong Hong, Jan-Jan Wu, Pen-Chung Yew, Wei-Chung Hsu, Chun-Chen Hsu, Pangfeng Liu, Chien-Min Wang and Yeh-Ching Chung, "Efficient and Retargetable Dynamic Binary Translation on Multicores," IEEE Transactions on Parallel and Distributed Systems (TPDS), volume 25, number 3, pages 622 - 632, March 2014. :::
Cai-Feng Lin, Ding-Yong Hong, Tzu-Hsien Tsai, Pangfeng Liu, Jan-Jan Wu, "A Grouping Algorithm for Training Tree-Shaped Models on Multiple GPUs with High Efficiency," IEEE International Conference on Computers, Software, and Applications (COMPSAC), IEEE, IEEE, Toronto, Canada, July 2025. :::
3.
Bing-Jou Wu, Ding-Yong Hong, Pangfeng Liu, Jan-Jan Wu, "Execution Time Optimization for Pipeline Deep Network Training on Multiple GPUs," Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), March 2025.
Scott Cheng, Mahmut Kandemir, Ding-Yong Hong, "Speculative Monte-Carlo Tree Search," Annual Conference on Neural Information Processing Systems (NeurIPS), December 2024.
6.
Ping-Han Tu, Yu-Che Cheng, Ding-Yong Hong, Pangfeng Liu, Jan-Jan Wu, "Approximation Algorithms and Simulated Annealing Heuristics for Row-And-Column Pruning of Deep Neural Networks," IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), November 2024. :::
7.
Chi-Yu Chiu, Ding-Yong Hong, Pangfeng Liu and Jan-Jan Wu, "Effective Compression of Language Models by Combining Pruning and Knowledge Distillation," IEEE International Conference on Computers, Software, and Applications (COMPSAC), IEEE, IEEE, Osaka, Japan, July 2024. :::
8.
Chao-Yu Lee, Ding-Yong Hong, Pangfeng Liu and Jan-Jan Wu, "Function Clustering to Optimize Resource Utilization on Container Platform," IEEE International Conference on Parallel and Distributed Systems, December 2023.
9.
Cheng-Hung Wu, Ding-Yong Hong, Pangfeng Liu and Jan-Jan Wu, "Exploiting Fine-Grained Structured Pruning for Efficient Inference on CNN Model," IEEE International Conference on Parallel and Distributed Systems, December 2023.
10.
Chien-Hung Lin, Ding-Yong Hong, Pangfeng Liu, Jan-Jan Wu, "Accelerate Inference of CNN Models on CPU via Column Combining Based on Simulated Annealing," the International Symposium on Computing and Networking, Japan, November 2023.
11.
Kung-Fu Chen and Ding-Yong Hong, "Rewriting Deep Learning Models for Maximizing Edge TPU Utilization," IEEE International Conference on Parallel and Distributed Systems (ICPADS), December 2022.
12.
Yi You, Pangfeng Liu, Ding-Yong Hong, Jan-Jan Wu and Wei-Chung Hsu, "Accelerating Convolutional Neural Networks via Inter-operator Scheduling," IEEE International Conference on Parallel and Distributed Systems (ICPADS), Best Paper Runner-up, December 2022. :::
13.
Yu-Jen Chang, Ding-Yong Hong, Pangfeng Liu, and Jan-Jan Wu, "Efficient Inference on Convolutional Neural Networks by Image Difficulty Prediction," IEEE International Conference on Big Data, the Machine learning with Big Data track., December 2022.
14.
Kuan-Wei Lu, Pangfeng Liu, Ding-Yong Hong, Jan-Jan Wu, "Efficient Dual Batch Size Deep Learning for Distributed Parameter Server Systems," IEEE Computers, Software, and Applications Conference (COMPSAC 2022, acceptance rate 22%), June 2022.
15.
Chang-Han Chiang, Pangfeng Liu, Da-Wei Wang, Ding-Yong Hong, and Jan-Jan Wu, "Optimal Branch Location Finding for Cost effective Inference on Branchynet," IEEE International Conference on Big Data (top conference), the Machine Learning with Big Data track, December 2021.
16.
An-Tai Chen, Pangfeng Liu, Ding-Yong Hong, and Jan-Jan Wu, "Accelerate CNN Models via Filter Pruning and Sparse Tensor Core," International Symposium on Computing and Networking, November 2021.
17.
Horng-Ruey Huang, Ding-Yong Hong, Jan-Jan Wu, Pangfeng Liu, Wei-Chung Hsu, "Efficient Video Captioning on Heterogeneous System Architectures," 35th IEEE International Parallel and Distributed Processing Symposium (IPDPS, top conference), Portland, Oregon USA (online), May 2021.
Sheng-Yu Fu, Chih-Min Lin, Ding-Yong Hong, Yu-Ping Liu, Jan-Jan Wu, Wei-Chung Hsu, "Exploiting SIMD Capability in an ARMv7-to-ARMv8 Dynamic Binary Translator," International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES), pages 1-3, Turin, Italy, September 2018.
22.
Chih-Min Lin, Sheng-Yu Fu, Ding-Yong Hong, Yu-Ping Liu, Jan-Jan Wu, Wei-Chung Hsu, "Exploiting SIMD Optimization in an ARMv7 Dynamic Binary Translator," Design Automation Conference, San Francisco, USA, June 2018.
Ding-Yong Hong, Sheng-Yu Fu, Yu-Ping Liu, Jan-Jan Wu, and Wei-Chung Hsu, "Exploiting Longer SIMD Lanes in Dynamic Binary Translation," IEEE International Conference on Parallel and Distributed Systems (ICPADS), December 2016, Best Paper (out of 412 submissions) :::
Sheng-Yu Fu, Ding-Yong Hong, Jan-Jan Wu, Pangfeng Liu and Wei-Chung Hsu, "SIMD Code Translation in an Enhanced HQEMU," IEEE International Conference on Parallel and Distributed Systems (ICPADS), December 2015. :::
28.
Yi-Hong Lyu, Ding-Yong Hong, Tai-Yi Wu, Jan-Jan Wu, Wei-Chung Hsu, Pangfeng Liu and Pen-Chung Yew, "DBILL: An Efficient and Retargetable Dynamic Binary Instrumentation Framework using LLVM Backend," ACM International Conference on Virtual Execution Environments (VEE), March 2014.
29.
Chun-Chen Hsu, Pangfeng Liu, Jan-Jan Wu, Pen-Chung Yew, Ding-Yong Hong, Wei-Chung Hsu and Chien-Min Wang, "Improving Dynamic Binary Optimization Through Early-Exit Guided Code Region Formation," ACM International Conference on Virtual Execution Environments (VEE), March 2013.
30.
Chun-Chen Hsu, Pangfeng Liu, Jan-Jan Wu, Pen-Chung Yew, Ding-Yong Hong, Wei-Chung Hsu and Chien-Min Wang, "Improving Region Selection Through Early-Exit Detection," Asia-Pacific Programming Languages and Compilers Workshop (APPLC), Beijing, China, June 2012.
31.
Ding-Yong Hong, Chun-Chen Hsu, Pen-Chung Yew, Jan-Jan Wu, Wei-Chung Hsu, Pangfeng Liu, Chien-Min Wang and Yeh-Ching Chung, "HQEMU: A Multi-Threaded and Retargetable Dynamic Binary Translator on Multicores," Proceedings of the Tenth International Symposium on Code Generation and Optimization (CGO), March 2012. :::
32.
Chun-Chen Hsu, Pangfeng Liu, Chien-Min Wang, Jan-Jan Wu, Ding-Yong Hong, Pen-Chung Yew and Wei-Chung Hsu, "LnQ: Building High Performance Dynamic Binary Translators with Existing Compiler Backends," International Conference on Parallel Processing (ICPP), September 2011.
33.
Ding-Yong Hong, Fang-Ping Pai, Shih-Hsiang Lo and Yeh-Ching Chung, "A Scalable HLA RTI System Based on Multiple-FedServ Architecture," International Conference on Computer Modelling and Simulation (UKSim), March 2010.
34.
Shih-Hsiang Lo, Cheng-An Chiu, Fang-Ping Pai, Ding-Yong Hong and Yeh-Ching Chung, "MGRID: A Modifiable- Grid Region Matching Approach for DDM in the HLA RTI," Spring Simulation Multiconference (SpringSim), March 2009.
35.
Seetharami Seelam, I-Hsin Chung, Ding-Yong Hong, Hui-Fang Wen and Hao Yu, "Early Experiences in Application Level I/O Tracing on Blue Gene Systems," IEEE International Parallel and Distributed Processing Symposium (IPDPS), April 2008.
36.
Ding-Yong Hong, Ching-Wen You and Yeh-Ching Chung, "An Efficient MPI-IO for Noncontiguous Data Access over InfiniBand," International Symposium on Parallel Architectures, Algorithms, and Networks (I-SPAN), December 2005.
