PhD, University of California, Los Angeles, 2014 - 2019
MS, University of California, Los Angeles, 2012 - 2014
BS, Southeast University, 2008 - 2012
Zhang, X., Wu, Y., Zhou, P., Tang, X., & Hu, J. (2021). Algorithm-hardware Co-design of Attention Mechanism on FPGA Devices. ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 20(5), 1-24.Association for Computing Machinery (ACM). doi: 10.1145/3477002.
Zhang, C., Sun, G., Fang, Z., Zhou, P., Pan, P., & Cong, J. (2019). Caffeine: Toward Uniformed Representation and Acceleration for Deep Convolutional Neural Networks. IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 38(11), 2072-2085.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TCAD.2017.2785257.
Tang, Y., Zhang, X., Zhou, P., & Hu, J. EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization. ACM Transactions on Design Automation of Electronic Systems.Association for Computing Machinery (ACM). doi: 10.1145/3505633.
Zhou, P., Sheng, J., Yu, C.H., Wei, P., Wang, J., Wu, D., & Cong, J. (2021). MOCHA. In The 2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, (pp. 273-279).ACM. doi: 10.1145/3431920.3439304.
Lo, M., Fang, Z., Wang, J., Zhou, P., Chang, M.C.F., & Cong, J. (2020). Algorithm-Hardware Co-design for BQSR Acceleration in Genome Analysis ToolKit. In 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).IEEE. doi: 10.1109/fccm48280.2020.00029.
Chi, Y., Cong, J., Wei, P., & Zhou, P. (2018). SODA. In Proceedings of the International Conference on Computer-Aided Design.ACM. doi: 10.1145/3240765.3240850.
Cong, J., Wei, P., Yu, C.H., & Zhou, P. (2018). Latte: Locality Aware Transformation for High-Level Synthesis. In 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).IEEE. doi: 10.1109/fccm.2018.00028.
Ruan, Z., He, T., Li, B., Zhou, P., & Cong, J. (2018). ST-Accel: A High-Level Programming Platform for Streaming Applications on FPGA. In 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).IEEE. doi: 10.1109/fccm.2018.00011.
Zhou, P., Ruan, Z., Fang, Z., Shand, M., Roazen, D., & Cong, J. (2018). Doppio: I/O-Aware Performance Analysis, Modeling and Optimization for In-memory Computing Framework. In 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).IEEE. doi: 10.1109/ispass.2018.00011.
Cong, J., Wei, P., Yu, C.H., & Zhou, P. (2017). Bandwidth Optimization Through On-Chip Memory Restructuring for HLS. In Proceedings of the 54th Annual Design Automation Conference 2017.ACM. doi: 10.1145/3061639.3062208.
Zhang, C., Fang, Z., Zhou, P., Pan, P., & Cong, J. (2016). Caffeine. In Proceedings of the 35th International Conference on Computer-Aided Design.ACM. doi: 10.1145/2966986.2967011.
Zhou, P., Park, H., Fang, Z., Cong, J., & DeHon, A. (2016). Energy Efficiency of Full Pipelining: A Case Study for Matrix Multiplication. In 2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).IEEE. doi: 10.1109/fccm.2016.50.
Cong, J., Huang, H., Ma, C., Xiao, B., & Zhou, P. (2014). A Fully Pipelined and Dynamically Composable Architecture of CGRA. In 2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines.IEEE. doi: 10.1109/fccm.2014.12.