論文誌
[1] Q. Cheng, L. Dai, M. Huang, A. Shen, W. Mao, M. Hashimoto, and H. Yu, "A Low-Power Sparse Convolutional Neural Network Accelerator with Pre-Encoding Radix-4 Booth Multiplier," IEEE Transactions on Circuits and Systems II, volume 70, number 6, 2246 - 2250, June 2023.
[2] T. Cheng, Y. Masuda, J. Chen, J. Yu, and M. Hashimoto, "Logarithm-Approximate Floating-Point Multiplier Is Applicable to Power-Efficient Neural Network Training," Integration, the VLSI Journal, volume 74, pages 19--31, September 2020.
国際会議
[1] T.-Y. Cheng, J. Yu, and M. Hashimoto, "Minimizing Power for Neural Network Training with Logarithm-Approximate Floating-Point Multiplier," Proceedings of International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS), July 2019.