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Songyun Qu (屈松云)

Short Bio

I am currently a fourth-year(at 2022) PhD candidate in Institute of Computing Technology, Chinese Academy of Sciences. My research interests primarily focus on Process in Memory (PIM)-systems, Energy Efficient NN Accelerator, Software/Hardware Co-Design, VLSI Design and AutoML.

Email: qusongyun18z@ict.ac.cn

Wechat: qusongyun

Tel: +8618811542553

Education

Publications

  1. [DAC’21] Sonyun Qu, Bing Li, Ying Wang, Lei Zhang, “ASBP: Automatic Structured Bit-Pruning for RRAM-based NN Accelerator,” in IEEE/ACM Proceedings of Design, Automation Conference, 2021.(CCF-A)
  2. [DAC’20] Sonyun Qu, Ying Wang, Bing Li, Xiandong Zhao, Dawen Xu Lei Zhang, “RaQu: An Automatic High-Utilization CNN Quantization and Mapping Framework for General-purpose RRAM Accelerator,” in IEEE/ACM Proceedings of Design, Automation Conference, 2020.(CCF-A)
  3. [DAC’22] Yintao He, Songyun Qu, Ying Wang, Bing Li, Huawei Li, Xiaowei Li, “InfoX: An Energy-Efficient ReRAM Accelerator Design with Information-Lossless Low-Bit ADCs”, to appear in IEEE/ACM Proceedings of Design, Automation Conference, 2022.(CCF-A)
  4. [DAC’22] Yuquan He, Songyun Qu, Gangliang Lin, Ying Wang, ChengLiu, LeiZhang, “Processing-in-SRAM Acceleration for Ultra-Low Power Visual 3DPerception”, to appear in IEEE/ACM Proceedings of Design, Automation Conference, 2022.(CCF-A)
  5. [TCAD’21] Bing Li, Songyun Qu, Ying Wang, “An Automated Quantization Framework for High-utilization RRAM-based PIM,” in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, doi: 10.1109/TCAD.2021.3061521, 2021.(CCF-A)
  6. [TC’21] Kaiwei Zou, Ying Wang, Long Cheng, Songyun Qu, Huawei Li, and Xiaowei Li, “CAP: Communication-aware Automated Parallelization for Deep Learning Inference on CMP Architectures,” in IEEE Transactions on Computers, 2021.(CCF-A)

Honors and Awards