Honglan Jiang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 33

Top Topics

Worst Case Scenario

Error Compensation

Top Venues

IEEE Trans. Circuits Syst. I Regul. Pap.

ACM Great Lakes Symposium on VLSI

IEEE Trans. Computers

Publications

Zijing Niu, Tingting Zhang, Honglan Jiang, Bruce F. Cockburn, Leibo Liu, Jie Han
Hardware-Efficient Logarithmic Floating-Point Multipliers for Error-Tolerant Applications. IEEE Trans. Circuits Syst. I Regul. Pap. 71 (1) (2024)
Xiaolu Hu, Ao Liu, Xinkuang Geng, Zizhong Wei, Kai Jiang, Honglan Jiang
A Configurable Approximate Multiplier for CNNs Using Partial Product Speculation. DATE (2024)
Wenhui Zhang, Xinkuang Geng, Qin Wang, Jie Han, Honglan Jiang
A Low-Power and High-Accuracy Approximate Adder for Logarithmic Number System. ACM Great Lakes Symposium on VLSI (2024)
Hai Mo, Yong Wu, Honglan Jiang, Zining Ma, Fabrizio Lombardi, Jie Han, Leibo Liu
Learning the Error Features of Approximate Multipliers for Neural Network Applications. IEEE Trans. Computers 73 (3) (2024)
Xinkuang Geng, Siting Liu, Jianfei Jiang, Kai Jiang, Honglan Jiang
Compact Powers-of-Two: An Efficient Non-Uniform Quantization for Deep Neural Networks. DATE (2024)
Zhican Wang, Gang Wang, Honglan Jiang, Ningyi Xu, Guanghui He
COSA:Co-Operative Systolic Arrays for Multi-head Attention Mechanism in Neural Network using Hybrid Data Reuse and Fusion Methodologies. DAC (2023)
Ziheng Wang, Farzad Niknia, Shanshan Liu, Honglan Jiang, Siting Liu, Pedro Reviriego, Fabrizio Lombardi
Feature-Embedding Triplet Networks with a Separately Constrained Loss Function. ISCAS (2023)
Tong Li, Honglan Jiang, Hai Mo, Jie Han, Leibo Liu, Zhi-Gang Mao
Approximate Processing Element Design and Analysis for the Implementation of CNN Accelerators. J. Comput. Sci. Technol. 38 (2) (2023)
Francisco Javier Hernandez Santiago, Honglan Jiang, Hussam Amrouch, Andreas Gerstlauer, Leibo Liu, Jie Han
Characterizing Approximate Adders and Multipliers for Mitigating Aging and Temperature Degradations. IEEE Trans. Circuits Syst. I Regul. Pap. 69 (11) (2022)
Han Li, Heng Shi, Honglan Jiang, Siting Liu
HSB-GDM: a Hybrid Stochastic-Binary Circuit for Gradient Descent with Momentum in the Training of Neural Networks. NANOARCH (2022)
Yibo Wu, Liang Wang, Xiaohang Wang, Jie Han, Jianfeng Zhu, Honglan Jiang, Shouyi Yin, Shaojun Wei, Leibo Liu
Upward Packet Popup for Deadlock Freedom in Modular Chiplet-Based Systems. HPCA (2022)
Yong Wu, Honglan Jiang, Zining Ma, Pengfei Gou, Yong Lu, Jie Han, Shouyi Yin, Shaojun Wei, Leibo Liu
An Energy-Efficient Approximate Divider Based on Logarithmic Conversion and Piecewise Constant Approximation. IEEE Trans. Circuits Syst. I Regul. Pap. 69 (7) (2022)
Honglan Jiang, Shaahin Angizi, Deliang Fan, Jie Han, Leibo Liu
Non-Volatile Approximate Arithmetic Circuits Using Scalable Hybrid Spin-CMOS Majority Gates. IEEE Trans. Circuits Syst. I Regul. Pap. 68 (3) (2021)
Zijing Niu, Honglan Jiang, Mohammad Saeed Ansari, Bruce F. Cockburn, Leibo Liu, Jie Han
A Logarithmic Floating-Point Multiplier for the Efficient Training of Neural Networks. ACM Great Lakes Symposium on VLSI (2021)
Honglan Jiang, Francisco Javier Hernandez Santiago, Hai Mo, Leibo Liu, Jie Han
Approximate Arithmetic Circuits: A Survey, Characterization, and Recent Applications. Proc. IEEE 108 (12) (2020)
Hao Cai, Honglan Jiang, Yongliang Zhou, Menglin Han, Bo Liu
Interplay Bitwise Operation in Emerging MRAM for Efficient In-memory Computing. CCF Trans. High Perform. Comput. 2 (3) (2020)
Zhixi Yang, Honglan Jiang, Xianbin Li, Jun Yang
Power-Efficient Approximate Multiplier Using Adaptive Error Compensation. ACM Great Lakes Symposium on VLSI (2020)
Honglan Jiang, Francisco J. H. Santiago, Mohammad Saeed Ansari, Leibo Liu, Bruce F. Cockburn, Fabrizio Lombardi, Jie Han
Characterizing Approximate Adders and Multipliers Optimized under Different Design Constraints. ACM Great Lakes Symposium on VLSI (2019)
Honglan Jiang, Leibo Liu, Fabrizio Lombardi, Jie Han
Low-Power Unsigned Divider and Square Root Circuit Designs Using Adaptive Approximation. IEEE Trans. Computers 68 (11) (2019)
Honglan Jiang, Leibo Liu, Pieter P. Jonker, Duncan G. Elliott, Fabrizio Lombardi, Jie Han
A High-Performance and Energy-Efficient FIR Adaptive Filter Using Approximate Distributed Arithmetic Circuits. IEEE Trans. Circuits Syst. I Regul. Pap. (1) (2019)
Honglan Jiang, Cong Liu, Fabrizio Lombardi, Jie Han
Low-Power Approximate Unsigned Multipliers With Configurable Error Recovery. IEEE Trans. Circuits Syst. I Regul. Pap. (1) (2019)
Hao Cai, Honglan Jiang, Menglin Han, Zhaohao Wang, You Wang, Jun Yang, Jie Han, Leibo Liu, Weisheng Zhao
Pj-AxMTJ: Process-in-memory with Joint Magnetization Switching for Approximate Computing in Magnetic Tunnel Junction. ISVLSI (2019)
Siting Liu, Honglan Jiang, Leibo Liu, Jie Han
Gradient Descent Using Stochastic Circuits for Efficient Training of Learning Machines. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37 (11) (2018)
Honglan Jiang, Leibo Liu, Fabrizio Lombardi, Jie Han
Adaptive approximation in arithmetic circuits: A low-power unsigned divider design. DATE (2018)
Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Honglan Jiang, Jie Han
Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error. IEEE Trans. Very Large Scale Integr. Syst. 26 (11) (2018)
Mohammad Saeed Ansari, Honglan Jiang, Bruce F. Cockburn, Jie Han
Low-Power Approximate Multipliers Using Encoded Partial Products and Approximate Compressors. IEEE J. Emerg. Sel. Topics Circuits Syst. 8 (3) (2018)
Weiqiang Liu, Liangyu Qian, Chenghua Wang, Honglan Jiang, Jie Han, Fabrizio Lombardi
Design of Approximate Radix-4 Booth Multipliers for Error-Tolerant Computing. IEEE Trans. Computers 66 (8) (2017)
Honglan Jiang, Leibo Liu, Jie Han
An efficient hardware design for cerebellar models using approximate circuits: special session paper. CODES+ISSS (2017)
Honglan Jiang, Cong Liu, Leibo Liu, Fabrizio Lombardi, Jie Han
A Review, Classification, and Comparative Evaluation of Approximate Arithmetic Circuits. ACM J. Emerg. Technol. Comput. Syst. 13 (4) (2017)
Honglan Jiang, Jie Han, Fei Qiao, Fabrizio Lombardi
Approximate Radix-8 Booth Multipliers for Low-Power and High-Performance Operation. IEEE Trans. Computers 65 (8) (2016)
Honglan Jiang, Cong Liu, Naman Maheshwari, Fabrizio Lombardi, Jie Han
A comparative evaluation of approximate multipliers. NANOARCH (2016)
Honglan Jiang, Chengkun Shen, Pieter P. Jonker, Fabrizio Lombardi, Jie Han
Adaptive Filter Design Using Stochastic Circuits. ISVLSI (2016)
Honglan Jiang, Jie Han, Fabrizio Lombardi
A Comparative Review and Evaluation of Approximate Adders. ACM Great Lakes Symposium on VLSI (2015)