Ming-Guang Lin

According to our database, Ming-Guang Lin authored at least 10 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

WS-CIM: Enabling Fast and Simultaneous Update for Multi-Macro Compute-in-Memory Architecture Using Weight Sharing Technique.

Yan-Ding Shieh, Ming-Guang Lin, Hung-Yu Wang, An-Yeu Andy Wu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2025

2024

Retraining-free Constraint-aware Token Pruning for Vision Transformer on Edge Devices.

Yun-Chia Yu, Mao-Chi Weng, Ming-Guang Lin, An-Yeu Andy Wu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Similarity-Aware Fast Low-Rank Decomposition Framework for Vision Transformers.

Yuan-June Luo, Yu-Shan Tai, Ming-Guang Lin, An-Yeu Andy Wu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

A 40nm 24.6TOPS/W Scalable EfficientDet Processor for Object Detection.

Yu-Chuan Chuang, Ming-Guang Lin, Chi-Tse Huang, Chieh-Fang Teng, Cheng-Yang Chang, Yi-Ta Chen, An-Yeu Andy Wu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

A 28nm 64.5TOPS/W Sparse Transformer Accelerator with Partial Product-based Speculation and Sparsity-Adaptive Computation.

Ming-Guang Lin, Jiing-Ping Wang, Yuan-June Luo, An-Yeu Andy Wu

Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2024

LATTE: Low-Precision Approximate Attention with Head-wise Trainable Threshold for Efficient Transformer.

Jiing-Ping Wang, Ming-Guang Lin, An-Yeu Andy Wu

Proceedings of the 6th IEEE International Conference on AI Circuits and Systems, 2024

Approximate Adder Tree Design with Sparsity-Aware Encoding and In-Memory Swapping for SRAM-based Digital Compute-In-Memory Macros.

Ming-Guang Lin, Jiing-Ping Wang, Cheng-Yang Chang, An-Yeu Andy Wu

Proceedings of the 6th IEEE International Conference on AI Circuits and Systems, 2024

2023

TSPTQ-ViT: Two-Scaled Post-Training Quantization for Vision Transformer.

Yu-Shan Tai, Ming-Guang Lin, An-Yeu Andy Wu

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

D-NAT: Data-Driven Non-Ideality Aware Training Framework for Fabricated Computing-In-Memory Macros.

Ming-Guang Lin, Chi-Tse Huang, Yu-Chuan Chuang, Yi-Ta Chen, Ying-Tuan Hsu, Yu-Kai Chen, Jyun-Jhe Chou, Tsung-Te Liu, Chi-Sheng Shih, An-Yeu Wu

IEEE J. Emerg. Sel. Topics Circuits Syst., 2022

Automated Quantization Range Mapping for DAC/ADC Non-linearity in Computing-In-Memory.

Chi-Tse Huang, Yu-Chuan Chuang, Ming-Guang Lin, An-Yeu Andy Wu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022