2024年度 発表文献一覧(入江・門本研究室)

雑誌論文

国際会議

    • ACM International Conference on Computing Frontiers (CF)
      1. Shun Nagasaki, Junichiro Kadomoto, Hidetsugu Irie, Shuichi Sakai:
        Multi-Tree Network Protocol Enabling System Partitioning for Shape-Changeable Computer System, ACM International Conference on Computing Frontiers (CF), Poster, May, 2024.
    • IEEE Symposium on Low-Power and High-Speed Chips and Systems (COOL Chips 27)
      1. Reoma Matsuo, Yuya Degawa, Hidetsugu Irie, Shuichi Sakai and Ryota Shioya:
        Branch Divergence-Aware Flexible Approximating Technique on GPUs, IEEE Symposium on Low-Power and High-Speed Chips and Systems (COOL Chips 27) , Reoma Matsuo, Yuya Degawa, Hidetsugu Irie, Shuichi Sakai and Ryota Shioya: “Branch Divergence-Aware Flexible Approximating Technique on GPUs,” Apr., 2024.
    • IEEE International Conference on QuantumComputing (QCE)
      1. Junichiro Kadomoto, Takuya Kasamura, Hidetsugu Irie:
        Preliminary Design Space Exploration for ASIC Implementation of Control Systems in Fault-Tolerant Quantum Computers, IEEE International Conference on Quantum Computing (QCE), Poster, Aug., 2024.
    • ACM Symposium on User Interface Software and Technology (UIST)
      1. Shoi To, Junichiro Kadomoto, Hidetsugu Irie, Shuichi Sakai:
        DataPipettor: Touch-Based Information Transfer Interface Using Proximity Wireless Communication, ACM Symposium on User Interface Software and Technology (UIST), Poster, Oct., 2024.
    • IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)
      1. Junichiro Kadomoto, Hidetsugu Irie, Shuichi Sakai:
        A Wireless Data and Power Transfer-Enabled MCU for Shape-Configurable Chiplet-Based Computers,IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), Nov., 2024.
      2. Tomohiro Yoshita, Junichiro Kadomoto, Hidetsugu Irie:
        A Dynamic Approximation Processor Based on Out-of-Order RISC-V in 28-nm CMOS, IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), Nov., 2024.

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  • オープンソースEDAフォーラム
    • 門本 淳一郎: オープンソースEDAと機械学習

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