Academic Profile : Faculty

Asst Prof Liu Weichen.JPG picture
Asst Prof Liu Weichen
Nanyang Assistant Professor, School of Computer Science and Engineering
 
External Links
 
Journal Articles
(Not applicable to NIE
staff as info will be
pulled from PRDS)
Shien Zhu, Luan H.K. Duong, Hui Chen, Di Liu, Weichen Liu, "FAT: An In-Memory Accelerator with Fast Addition for Ternary Weight Neural Networks", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022.

Xiangzhong Luo, Di Liu, Hao Kong, Shuo Huai, Hui Chen, Weichen Liu, “SurgeNAS: A Comprehensive Surgery on Hardware-Aware Differentiable Neural Architecture Search”, IEEE Transactions on Computers (TC), 2022.

Hui Chen, Peng Chen, Xiangzhong Luo, Shuo Huai, Weichen Liu, “LAMP: Load-balanced Multipath Parallel Transmission in Point-to-point NoCs”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022.

Shien Zhu, Luan H. K. Duong, Weichen Liu, “TAB: Unified and Optimized Ternary, Binary and Mixed-Precision Neural Network Inference on the Edge”, ACM Transactions on Embedded Computing Systems (TECS), 2022.

Peng Chen, Hui Chen, Jun Zhou, Mengquan Li, Weichen Liu, Chunhua Xiao, Yiyuan Xie, Nan Guan, “Contention Minimization in Emerging SMART NoC via Direct and Indirect Routes”, IEEE Transactions on Computers (TC), 2021.

Pengxing Guo, Weigang Hou, Lei Guo, Luan H. K. Duong, Weichen Liu, “Fault-Tolerant Routing Mechanism in 3D Optical Network-on-Chip based on Node Reuse”, IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), 2020.
Book Chapters
(Not applicable to NIE
staff as info will be
pulled from PRDS)
Di Liu, Hao Kong, Xiangzhong Luo, Shuo Huai, Weichen Liu, “Edge Intelligence: From Deep Learning’s Perspective”, The Key Elements of Digital Factory, Elsevier, 2022.

Mengquan Li, Weichen Liu, “Thermal Reliability and Communication Performance Co-Optimization for WDM-based Optical Networks-on-Chip”, Silicon Photonics for High Performance Computing and Beyond, CRC Press, 2021.
Conference Papers
(Not applicable to NIE
staff as info will be
pulled from PRDS)
Xiangzhong Luo, Di Liu, Hao Kong, Shuo Huai, Hui Chen, Weichen Liu, “You Only Search Once: On Lightweight Differentiable Architecture Search for Resource-Constrained Embedded Platforms”, ACM/IEEE Design Automation Conference (DAC), 2022. (Publicity Paper)

Shiqing Li, Di Liu, Weichen Liu, “Optimized Data Reuse via Reordering for Sparse Matrix-Vector Multiplication on FPGAs”, ACM/IEEE International Conference on Computer Aided Design (ICCAD), 2021.

Shuo Huai, Lei Zhang, Di Liu, Weichen Liu, Ravi Subramaniam, “ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems”, ACM/IEEE Design Automation Conference (DAC), 2021.

Mengquan Li, Jun Zhou, Pengxing Guo, Weichen Liu, “Lightweight Thermal Monitoring in Optical Networks-on-Chip via Router Reuse”, ACM/IEEE Design, Automation and Test in Europe (DATE), 2020.

Weichen Liu, Wenyang Liu, Yichen Ye, Qian Lou, Yiyuan Xie, Lei Jiang, “Holylight: A Nanophotonic Accelerator for Deep Learning in Data Centers”, ACM/IEEE Design, Automation and Test in Europe (DATE), 2019.

Mengquan Li, Weichen Liu, Lei Yang, Peng Chen, Duo Liu, Nan Guan, “Routing in Optical Network-on-Chip: Minimizing Contention with Guaranteed Thermal Reliability”, ACM/IEEE Asia and South Pacific Design Automation Conference (ASPDAC), 2019. (Best Paper Candidate Award)
 
Scopus