Publications

Jinming Zhuang, Zhuoping Yang, Peipei Zhou (2023). High Performance, Low Power Matrix Multiply Design on ACAP: from Architecture, Design Challenges and DSE Perspectives (🔥📣New Paper & Project🔥📣! ). To appear in Proceedings of the 60th ACM/IEEE Design Automation Conference, San Francisco, California, USA, (DAC ’23), July 9–13, 2023, San Francisco, CA, USA. Full Paper Accepted (acceptance ratio is 23 percent).

Jinming Zhuang, Jason Lau, Hanchen Ye, Zhuoping Yang, Yubo Du, Jack Lo, Kristof Denolf, Stephen Neuendorffer, Alex K. Jones, Jingtong Hu, Deming Chen, Jason Cong, Peipei Zhou (2023). CHARM: Composing Heterogeneous AcceleRators for Matrix Multiply on Versal ACAP Architecture (🔥📣New Paper & Project🔥📣! ). Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA ’23), February 12–14, 2023, Monterey, CA, USA. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3543622.3573210.

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Sébastien Ollivier, Sheng Li, Yue Tang, Chayanika Chaudhuri, Peipei Zhou, Xulong Tang, Jingtong Hu, Alex K. Jones (2022). Sustainable AI Processing at the Edge. IEEE Micro.

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Xinyi Zhang, Cong Hao, Peipei Zhou, Alex Jones, Jingtong Hu (2022). H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication Awareness. 2022 Design Automation Conference (DAC 2022).

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Yue Tang, Xinyi Zhang, Peipei Zhou, Jingtong Hu (2022). EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization. 2022 ACM Transactions on Design Automation of Electronic Systems (TODAES 22).

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Xinyi Zhang, Yawen Wu, Peipei Zhou, Xulong Tang, Jingtong Hu (2021). Algorithm-hardware Co-design of Attention Mechanism on FPGA Devices. ACM Transactions on Embedded Computing Systems (TECS 21).

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Peipei Zhou, Jiayi Sheng, Cody Hao Yu, Peng Wei, Jie Wang, Di Wu, Jason Cong (2021). MOCHA: Multinode Cost Optimization in Heterogeneous Clouds with Accelerators. 2021 ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA 21).

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Michael Lo, Zhenman Fang, Jie Wang, Peipei Zhou, Mau-Chung Frank Chang, Jason Cong (2020). Algorithm-Hardware Co-design for BQSR Acceleration in Genome Analysis ToolKit. 2020 IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 20).

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Peipei Zhou (2019). Modeling and Optimization for Customized Computing: Performance, Energy and Cost Perspective. UCLA Electronic Theses and Dissertations.

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Chen Zhang, Guangyu Sun, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong (2018). Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks (🔥Best Paper). IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ( Volume: 38, Issue: 11, Nov. 2019).

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Yuze Chi, Jason Cong, Peng Wei, Peipei Zhou (2018). SODA: Stencil with Optimized Dataflow Architecture (🔥Best Paper Nominee). 2018 International Conference On Computer Aided Design (ICCAD 18).

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Jason Cong, Zhenman Fang, Yuchen Hao, Peng Wei, Cody Hao Yu, Chen Zhang, Peipei Zhou (2018). Best-effort FPGA programming: a few steps can go a long way. arXiv.

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Peipei Zhou, Zhenyuan Ruan, Zhenman Fang, Megan Shand, David Roazen, Jason Cong (2018). Doppio: I/O-Aware Performance Analysis, Modeling and Optimization for In-Memory Computing Framework(🔥Best Paper Nominee). 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 18).

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Jason Cong, Peng Wei, Cody Hao Yu, Peipei Zhou (2018). Latte: Locality Aware Transformation for High-Level Synthesis. 2018 IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 18), short paper acceptance ratio: 7/48 = 14.6%.

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Zhenyuan Ruan, Tong He, Bojie Li, Peipei Zhou, Jason Cong (2018). ST-Accel: A High-Level Programming Platform for Streaming Applications on FPGA. 2018 IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 18), full paper acceptance ratio: 22/106 = 20.7%.

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Jason Cong, Peng Wei, Cody Hao Yu, Peipei Zhou (2017). Bandwidth Optimization Through On-Chip Memory Restructuring for HLS. 54th Annual Design Automation Conference (ACM DAC 17), acceptance rate: 161/676 = 24%.

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Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong (2016). Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks. 36th International Conference on Computer-Aided Design (ACM ICCAD 16), acceptance rate: 97/408 = 23.8%.

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Peipei Zhou, Hyunseok Park, Zhenman Fang, Jason Cong, André DeHon (2016). Energy Efficiency of Full Pipelining: A Case Study for Matrix Multiplication. 24th IEEE International Symposium on Field-Programmable Custom Computing Machines (IEEE FCCM 16), acceptance rate: 32/133 = 24%.

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Yu-Ting Chen, Jason Cong, Zhenman Fang, Peipei Zhou (2016). ARAPrototyper: Enabling Rapid Prototyping and Evaluation for Accelerator-Rich Architecture. 24th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (ACM/SIGDA FPGA 16).

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Yu-Ting Chen, Jason Cong, Jie Lei, Sen Li, Myron Peto, Paul Spellman, Peng Wei, Peipei Zhou (2015). CS-BWAMEM: A fast and scalable read aligner at the cloud scale for whole genome sequencing. High Throughput Sequencing, Algorithms & Applications, A SIG of IMSB/ECCB 2015.

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Peipei Zhou (2014). A Fully Pipelined and Dynamically Composable Architecture of CGRA (Coarse Grained Reconfigurable Architecture). UCLA Electronic Theses and Dissertations.

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Jason Cong, Hui Huang, Chiyuan Ma, Bingjun Xiao, Peipei Zhou (2014). A Fully Pipelined and Dynamically Composable Architecture of CGRA. 22nd IEEE International Symposium on Field-Programmable Custom Computing Machines (IEEE FCCM 14).

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