An Efficient MPI-IO for Noncontiguous Data Access over InfiniBand. - Ding-Yong Hong; Ching-Wen You; Yeh-Ching Chung (ISPAN, 2005)

Early experiences in application level I/O tracing on blue gene systems. - Seetharami R. Seelam; I-Hsin Chung; Ding-Yong Hong; Hui-Fang Wen; Hao Yu 008 (IPDPS, 2008)

MGRID: a modifiable-grid region matching approach for DDM in the HLA RTI. - Shih-Hsiang Lo; Cheng-An Chiu; Fang-Ping Pai; Ding-Yong Hong; Yeh-Ching Chung (SpringSim, 2009)

A Scalable HLA RTI System Based on Multiple-FedServ Architecture. - Ding-Yong Hong; Fang-Ping Pai; Shih-Hsiang Lo; Yeh-Ching Chung (UKSim, 2010)

LnQ: Building High Performance Dynamic Binary Translators with Existing Compiler Backends. - Chun-Chen Hsu; Pangfeng Liu; Chien-Min Wang; Jan-Jan Wu; Ding-Yong Hong; Pen-Chung Yew; Wei-Chung Hsu (ICPP, 2011)

HQEMU: a multi-threaded and retargetable dynamic binary translator on multicores. - Ding-Yong Hong; Chun-Chen Hsu; Pen-Chung Yew; Jan-Jan Wu; Wei-Chung Hsu; Pangfeng Liu; Chien-Min Wang; Yeh-Ching Chung (CGO, 2012)

Improving dynamic binary optimization through early-exit guided code region formation. - Chun-Chen Hsu; Pangfeng Liu; Jan-Jan Wu; Pen-Chung Yew; Ding-Yong Hong; Wei-Chung Hsu; Chien-Min Wang (VEE, 2013)

DBILL: an efficient and retargetable dynamic binary instrumentation framework using llvm backend. - Yi-Hong Lyu; Ding-Yong Hong; Tai-Yi Wu; Jan-Jan Wu; Wei-Chung Hsu; Pangfeng Liu; Pen-Chung Yew (VEE, 2014)

Efficient and Retargetable Dynamic Binary Translation on Multicores. - Ding-Yong Hong; Jan-Jan Wu; Pen-Chung Yew; Wei-Chung Hsu; Chun-Chen Hsu; Pangfeng Liu; Chien-Min Wang; Yeh-Ching Chung (IEEE Trans. Parallel Distributed Syst., 2014)

SIMD Code Translation in an Enhanced HQEMU. - Sheng-Yu Fu; Ding-Yong Hong; Jan-Jan Wu; Pangfeng Liu; Wei-Chung Hsu (ICPADS, 2015)

A dynamic binary translation system in a client/server environment. - Chun-Chen Hsu; Ding-Yong Hong; Wei-Chung Hsu; Pangfeng Liu; Jan-Jan Wu (J. Syst. Archit., 2015)

Exploiting Longer SIMD Lanes in Dynamic Binary Translation. - Ding-Yong Hong; Sheng-Yu Fu; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (ICPADS, 2016)

Optimizing Control Transfer and Memory Virtualization in Full System Emulators. - Ding-Yong Hong; Chun-Chen Hsu; Cheng-Yi Chou; Wei-Chung Hsu; Pangfeng Liu; Jan-Jan Wu (ACM Trans. Archit. Code Optim., 2016)

Exploiting Asymmetric SIMD Register Configurations in ARM-to-x86 Dynamic Binary Translation. - Yu-Ping Liu; Ding-Yong Hong; Jan-Jan Wu; Sheng-Yu Fu; Wei-Chung Hsu (PACT, 2017)

Dynamic translation of structured Loads/Stores and register mapping for architectures with SIMD extensions. - Sheng-Yu Fu; Ding-Yong Hong; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (LCTES, 2017)

Exploiting SIMD capability in an ARMv7-to-ARMv8 dynamic binary translator. - Sheng-Yu Fu; Chih-Min Lin; Ding-Yong Hong; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (CASES, 2018)

Dynamic tuning of applications using restricted transactional memory. - Shih-Kai Lin; Ding-Yong Hong; Sheng-Yu Fu; Jan-Jan Wu; Wei-Chung Hsu (RACS, 2018)

Efficient and retargetable SIMD translation in a dynamic binary translator. - Sheng-Yu Fu; Ding-Yong Hong; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (Softw. Pract. Exp., 2018)

Improving SIMD Parallelism via Dynamic Binary Translation. - Ding-Yong Hong; Yu-Ping Liu; Sheng-Yu Fu; Jan-Jan Wu; Wei-Chung Hsu (ACM Trans. Embed. Comput. Syst., 2018)

Exploiting Vector Processing in Dynamic Binary Translation. - Chih-Min Lin; Sheng-Yu Fu; Ding-Yong Hong; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (ICPP, 2019)

Optimizing data permutations in structured loads/stores translation and SIMD register mapping for a cross-ISA dynamic binary translator. - Sheng-Yu Fu; Ding-Yong Hong; Yu-Ping Liu; Jan-Jan Wu; Wei-Chung Hsu (J. Syst. Archit., 2019)

Processor-Tracing Guided Region Formation in Dynamic Binary Translation. - Ding-Yong Hong; Jan-Jan Wu; Yu-Ping Liu; Sheng-Yu Fu; Wei-Chung Hsu (ACM Trans. Archit. Code Optim., 2019)

Exploiting SIMD Asymmetry in ARM-to-x86 Dynamic Binary Translation. - Yu-Ping Liu; Ding-Yong Hong; Jan-Jan Wu; Sheng-Yu Fu; Wei-Chung Hsu (ACM Trans. Archit. Code Optim., 2019)

Optimal Branch Location for Cost-effective Inference on Branchynet. - Chang-Han Chiang; Pangfeng Liu; Da-Wei Wang 004; Ding-Yong Hong; Jan-Jan Wu (IEEE BigData, 2021)

Accelerate CNN Models via Filter Pruning and Sparse Tensor Core. - An-Tai Chen; Pangfeng Liu; Ding-Yong Hong; Jan-Jan Wu (CANDAR, 2021)

Efficient Video Captioning on Heterogeneous System Architectures. - Horng-Ruey Huang; Ding-Yong Hong; Jan-Jan Wu; Pangfeng Liu; Wei-Chung Hsu (IPDPS, 2021)

Efficient Inference on Convolutional Neural Networks by Image Difficulty Prediction. - Yu-Jen Chang; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (IEEE Big Data, 2022)

Efficient Dual Batch Size Deep Learning for Distributed Parameter Server Systems. - Kuan-Wei Lu; Pangfeng Liu; Ding-Yong Hong; Jan-Jan Wu (COMPSAC, 2022)

Rewriting Deep Learning Models for Maximizing Edge TPU Utilization. - Kung-Fu Chen; Ding-Yong Hong (ICPADS, 2022)

Accelerating Convolutional Neural Networks via Inter-operator Scheduling. - Yi You; Pangfeng Liu; Ding-Yong Hong; Jan-Jan Wu; Wei-Chung Hsu (ICPADS, 2022)

CNN Models Acceleration Using Filter Pruning and Sparse Tensor Core. - Hong-Xuan Wei; Pangfeng Liu; Ding-Yong Hong; Jan-Jan Wu; An-Tai Chen (Int. J. Netw. Comput., 2022)

Accelerating Video Captioning on Heterogeneous System Architectures. - Horng-Ruey Huang; Ding-Yong Hong; Jan-Jan Wu; Kung-Fu Chen; Pangfeng Liu; Wei-Chung Hsu (ACM Trans. Archit. Code Optim., 2022)

Accelerate Inference of CNN Models on CPU via Column Combining Based on Simulated Annealing. - Chien-Hung Lin; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (candar, 2023)

Function Clustering to Optimize Resource Utilization on Container Platform. - Chao-Yu Lee; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (ICPADS, 2023)

Exploiting Fine-Grained Structured Pruning for Efficient Inference on CNN Model. - Cheng-Hung Wu; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (ICPADS, 2023)

Effective Compression of Language Models by Combining Pruning and Knowledge Distillation. - Chi-Yu Chiu; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (COMPSAC, 2024)

Approximation Algorithms and Simulated Annealing Heuristics for Row-and-Column Pruning of Deep Neural Networks. - Ping-Han Tu; Yu-Che Cheng; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (ISPA, 2024)

Speculative Monte-Carlo Tree Search. - Scott Cheng; Mahmut T. Kandemir; Ding-Yong Hong (NeurIPS, 2024)

Execution Time Optimization for Pipeline Deep Network Training on Multiple GPUs. - Bing-Jou Wu; Ding-Yong Hong; Pangfeng Liu; Jan-Jan Wu (PDP, 2025)

Optimizing Compute Core Assignment for Dynamic Batch Inference in AI Inference Accelerator. - Ze-Wei Liou; Ding-Yong Hong (SAC, 2025)

GPU memory usage optimization for backward propagation in deep network training. - Ding-Yong Hong; Tzu-Hsien Tsai; Ning Wang; Pangfeng Liu; Jan-Jan Wu (J. Parallel Distributed Comput., 2025)

Efficient Column-Wise N:M Pruning on RISC-V CPU. - Chi-Wei Chu; Ding-Yong Hong; Jan-Jan Wu (CoRR, 2025)