Ding, Caiwen

FTRANS: energy-efficient acceleration of transformers using FPGA

Li, B., Pandey, S., Fang, H., Lyv, Y., Li, J., Chen, J., Xie, M., Wan, L., Liu, H., & Ding, C. (2020) · Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 206

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning

Peng, H., Huang, S., Geng, T., Li, A., Jiang, W., Liu, H., Wang, S., & Ding, C. (2021) · 2021 22nd International Symposium on Quality Electronic Design (ISQED)

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 105

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining

Peng, H., Huang, S., Chen, S., Li, B., Geng, T., Li, A., Jiang, W., Wen, W., Bi, J., Liu, H., et al. (2022) · Proceedings of the 59th ACM/IEEE Design Automation Conference

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 48

QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity

Stein, S. A., Baheri, B., Chen, D., Mao, Y., Guan, Q., Li, A., Xu, S., & Ding, C. (2021) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 41

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

Tang, S., Wang, Y., Kong, Z., Zhang, T., Li, Y., Ding, C., Wang, Y., Liang, Y., & Xu, D. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 37

HMC-T RAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU

Huang, S., Chen, S., Peng, H., Manu, D., Kong, Z., Yuan, G., Yang, L., Wang, S., Liu, H., & Ding, C. (2021) · Proceedings of the 2021 Great Lakes Symposium on VLSI

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 4