Jieming Yin is a Professor with the School of Computer Science, Nanjing University of Posts and Telecommunications, China. He obtained his PhD degree from University of Minnesota, Twin Cities in 2015. Dr. Yin was a faculty member at Lehigh University, and a researcher at AMD. His research interests lie in computer architecture, with emphasis on SoC system integration, network on chips, and machine learning aided computer system design. Dr. Yin received the Jiangsu Distinguished Professor Award in 2022. His work has been recognized with NOCS 2020 Best Paper Award, and DAC 2021 Best Paper Award Nomination. His research on modular-routing design for chiplet-based systems was featured in IEEE Spectrum. Dr. Yin has published papers in top-tier conference venues including ISCA, HPCA, MICRO, DAC, NeurIPS, and ICML, and holds over 10 U.S. patents and patent applications.
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Aug. 2023: Paper "QuCT: A Framework for Analyzing Quantum Circuit by Extracting Contextual and Topological Features" accepted in MICRO'23
Jul. 2023: Paper "Monad: Towards Cost-effective Specialization for Chiplet-based Spatial Accelerators" accepted in ICCAD'23
Apr. 2023: Paper "COLA: Orchestrating Error Coding and Learning for Robust Neural Network Inference Against Hardware Defects" accepted in ICML'23
Mar. 2023: Paper "Rubick: A Synthesis Framework for Spatial Architectures via Dataflow Decomposition" accepted in DAC'23
Jan. 2023: Paper "CompoundEye: A 0.24-4.17 TOPS Scalable Multi-Node DNN Processor for Image Recognition" accepted in ISCAS'23
Oct. 2022: Paper "Trans-FW: Short Circuiting Page Table Walk in Multi-GPU Systems via Remote Forwarding" accepted in HPCA'23
Oct. 2022: Paper "NeuroPots: Realtime Proactive Defense against Bit-Flip Attacks in Neural Networks" accepted in USENIX Security'23
Sep. 2022: Paper "CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference" accepted in NeurIPS'22
Sep. 2021: Paper "Improving Address Translation in Multi-GPUs via Sharing and Spilling aware TLB Design" accepted in MICRO'21
Mar. 2021: Paper "TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation" accepted in ISCA'21
Feb. 2021: Paper "Distilling Arbitration Logic from Traces using Machine Learning: A Case Study on NoC" accepted in DAC'21
Nov. 2020: Paper "Designing a Cost-Effective Cache Replacement Policy using Machine Learning" accepted in HPCA'21