Peipei Zhou

  • (2019) 2019 TCAD Donald O. Pederson Best Paper Award.
  • (2018) 2018 ICCAD Best Paper Nominee.
  • (2018) 2018 Phi Tau Phi Scholarship.
  • (2018) 2018 ISPASS Best Paper Nominee.

  • PhD, University of California, Los Angeles, 2014 - 2019
  • MS, University of California Los Angeles, 2012 - 2014

  • 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.

  • 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), 00, (pp. 157-166).Institute of Electrical and Electronics Engineers (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, (pp. 1-8).Association for Computing Machinery (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), (pp. 125-128).Institute of Electrical and Electronics Engineers (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), (pp. 9-16).Institute of Electrical and Electronics Engineers (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), (pp. 22-32).Institute of Electrical and Electronics Engineers (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, (pp. 1-6).Association for Computing Machinery (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, (pp. 1-8).Association for Computing Machinery (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), (pp. 172-175).Institute of Electrical and Electronics Engineers (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, (pp. 9-16).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/fccm.2014.12.