2025:

• [ISCA 2025] C.Wu*, R.Song*, C.Liu, P.Haghi, A.Li, M.Huang, T.Geng: "DS-TPU: Dynamical System for on-Device Lifelong Graph Learning with Nonlinear Node Interaction", the 52nd IEEE/ACM International Symposium on Computer Architecture.

• [DAC 2025] P.Haghi, A.Falahati, Z.Azad, C.Wu, R.Song, C.Liu, A.Li, T.Geng: "DM-Tune: Quantizing Diffusion Models with Mixture-of-Gaussian Guided Noise Tuning", The 61st Design Automation Conference.

• [ICML 2025] C.Liu, C.Wu, R.Song, A.Li, Y.Wu, T.Geng: "An Expressive and Self-Adaptive Dynamical System for Efficient Equation Learning", Forty-third International Conference on Machine Learning.

• [ICLR 2025] C.Liu, C.Wu, S.Cao, M.Chen, J.Liang, A.Li, M.Huang, C.Ren, Y.Wu, D.Liu, T.Geng: "Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models", The Thirteenth International Conference on Learning Representations.

• [ICLR 2025] C.Liu, R.Song, C.Wu, P.Haghi, T.Geng: "InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems", The Thirteenth International Conference on Learning Representations.

• [ICLR 2025] R.Song, C.Liu, C.Wu, D.Liu, Y.Wu, T.Geng: "Beyond-Moore LLM: Uncovering a New Type of Compute Resource for LLM Training with Revolutionary Computing Efficiency", The Thirteenth International Conference on Learning Representations.

• [ICLR 2025] G.Sun, M.Jin, Z.Wang, C.Wang, S.Ma, Q.Wang, T.Geng, Y.Wu, Y.Zhang, D.Liu: "Visual Agents as Fast and Slow Thinkers", The Thirteenth International Conference on Learning Representations.

• [ATC 2025] Y.Wang, B.Feng, Z.Wang, T.Geng, A.Li, Y.Ding: "GMI-DRL: Empowering Multi-GPU DRL with Adaptive-Grained Parallelism", 2025 USENIX Annual Technical Conference.

• [ICS 2025] A. Guo, Y. Hao, X. Yao, S. Yang, J. Huang, T. Geng, M. Herbordt: "SmartNIC-GPU-CPU Heterogeneous System for Large Machine Learning Model with Software-Hardware Codesign", the 39th ACM International Conference on Supercomputing.

​   2024:

• [ISCA 2024] R.Song*, C.Wu*, C.Liu, A.Li, M.Huang, T.Geng: "DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems", the 51st IEEE/ACM International Symposium on Computer Architecture.

• [MICRO 2024] P.Haghi, C.Wu, Z.Azad, Y.Li, A.Gui, Y.Hao, A.Li, T.Geng: "Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign", 57th IEEE/ACM International Symposium on Microarchitecture.

• [ICLR 2024] C.Wu, R.Song, C.Liu, Y.Yang, A.Li, M.Huang, T.Geng: "Extending Power of Nature from Binary to Real-valued Graph Learning in Real World", The Twelfth International Conference on Learning Representations.

•  

• [NeurIPS 2024] R.Zeng, C.Han, Q.Wang, C.Wu, T.Geng, L.Huang, Y.Wu, D.Liu: "Visual Fourier Prompt Tuning", Thirty-eighth Conference on Neural Information Processing Systems.

• [ICML 2024] C.Han, Y.Lu, G.Sun, J.Liang, Z.Cao, Q.Wang, Q.Guan, S.Dianat, R.Rao, T.Geng, Z.Tao, D.Liu "Prototypical Transformer As Unified Motion Learners", Forty-second International Conference on Machine Learning.

• [TC 2024] C.Wu, A.Guo, P.Haghi, A.Li, T.Geng, M.Herbordt: "FPGA-Accelerated Range-Limited Molecular Dynamics", IEEE Transactions on Computers.

• [Briefings in Bioinformatics 2024] Y.Wang, J.Zhao, H.Xu, C.Han, Z.Tao, D.Zhou, T.Geng, D.Liu, Z.Ji: "A systematic evaluation of computational methods for cell segmentation", Briefings in Bioinformatics (Impact Factor: 13.99).

• [AIS 2024] Y.Li, J.Liu, X.Zhao, W.Liu, T.Geng, A.Li, X.Zhang: "Accurate and Data-Efficient Micro-XRD Phase Identification Using Multi-Task Learning: Application to Hydrothermal Fluids", Advanced Intelligent Systems Journal (Impact Factor: 7.4).

• [SC 2024] H.Feng, B.Zhang, F.Ye, M.Si, C.Chu, J.Tian, C.Yin, Z.Deng, Y.Hao, P.Balaji, T.Geng, D.Tao: "Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression", Proceedings of the International Conference for High-Performance Computing, Networking, Storage, and Analysis.

• [ICS 2024] P.Haghi, C.Tan, A.Guo, C.Wu, D.Liu, A.Li, A.Skjellum, T.Geng, M.Herbordt: "SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications", the 38th ACM International Conference on Supercomputing.

    2023:

• [DAC 2023] Z.Liu, Y.Yang, Z.Pan, A.Sharma, A.Hasan, C.Ding, A.Li, M.Huang, T.Geng: "Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning", The 59th Design Automation Conference.

• [DAC 2023] Y.Luo*, C.Tan*, N.Agostini, A.Li, A.Tumeo, N.Dave, T.Geng: "ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs", The 59th Design Automation Conference.

• [AAAI 2023] Z.Pan, A.Sharma, J.Hu, Z.liu, A.Li, H.Liu, M.Huang, T.Geng: "Ising-Traffic: An Ising-based Framework for Traffic Congestion Prediction with Uncertainty", Thirty-Seventh AAAI Conference on Artificial Intelligence.

• [ICS 2023] A.Guo, Y.Hao, C.Wu, P.Haghi, Z.Pan, M.Si, D.Tao, A.Li, M.Herbordt, T.Geng: "Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training", the 36th ACM International Conference on Supercomputing.

• [MICRO 2023] U.Vengalam, Y.Liu, T.Geng, H.Wu, M.Huang: "Supporting Energy-Based Learning With an Ising Machine Substrate: A Case Study on RBM", the 56th IEEE/ACM International Symposium on Microarchitecture.

• [SC 2023] C.Wu, T.Geng, A.Guo, S.Bandara, P.Haghi, C.Liu, A.Li, M.Herbordt: "FASDA: An FPGA-Aided, Scalable and Distributed Accelerator for Range-Limited Molecular Dynamics", Proceedings of the International Conference for High-Performance Computing, Networking, Storage, and Analysis.

• [OSDI 2023] Y.Wang, B.Feng, Z.Wang, T.Geng, A.Li, K.Barker, Y.Ding: "MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms", USENIX Symposium on Operating Systems Design and Implementation.

• [ICS 2023] P.Haghi, W.Krska, C.Tan, T.Geng, ..., A.Li, A.Skjellum, M.Herbordt: "FLASH: FPGA-Accelerated Smart Switches with GCN Case Study", the 36th ACM International Conference on Supercomputing.

• [DAC 2023] H.Peng, ..., C.Wang, T.Geng, W.Wen, X.Xu, C.Ding: "PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment", The 59th Design Automation Conference.

• [NeurIPS 2023] J.Liang, Y.Cui, Q.Wang, T.Geng, W.Wang, D.Liu: "ClusterFomer: Clustering As A Universal Visual Learner", Thirty-seventh Conference on Neural Information Processing Systems.

• [NeurIPS 2023] H.Peng, R.Ran, ..., T.Geng, X.Xu, W.Wen, C.Ding: "LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference", Thirty-seventh Conference on Neural Information Processing Systems.​ ​

• [ICCV 2023] H.Peng, S.Huang, ..., T.Geng, K.Mahmood, W.Wen, X.Xu, C.Ding: "AutoReP: Automatic ReLU Replacement for Fast Private Network Inference", 2023 International Conference on Computer Vision.

• [TIP 2023] D.Liu, J.Liang, T.Geng, A.Loui, T.Zhou: "Tripartite Feature Enhanced Pyramid Network for Dense Prediction", IEEE Transactions on Image Processing (Impact Factor: 10.86).

• [CVPR 2023] Y.Lu, Q.Wang, S.Ma, T.Geng, Y.Chen, H.Chen, D.Liu: "TransFlow: Transformer as Flow Learner", Conference on Computer Vision and Pattern Recognition 2023.

​   2022:​

• [TPDS 2022] W.Sun, A.Li, T.Geng, S.Stuijk, H.Corporaal: "Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numerical Behaviors", IEEE Transactions on Parallel and Distributed Systems.

• [HPCA 2022] H.You*, T.Geng*, Y.Zhang, A.Li, Y.Lin: "GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design", The 28th IEEE International Symposium on HighPerformance Computer Architecture.

• [HPCA 2022] C.Tan, N.B.Agostini, T.Geng, C.Xie, J.Li, A.Li, K.Barker, A.Tumeo: "DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs", The 28th IEEE International Symposium on High-Performance Computer Architecture.

• [DAC 2022] H. Peng, ..., T.Geng, ..., C.Ding: "A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining", The 58th Design Automation Conference.​

• [ICS 2022] C.Zhang, S.Jin, T.Geng, J.Tian, A.Li, D.Tao: "Accelerating Parallel I/O Via Hardware-Algorithm Co-Designed Adaptive Lossy Compression", the 36th ACM International Conference on Supercomputing.

• [ICS 2022] C.Tan, T.Tembe, J.Zhang, B.Fang, T.Geng, G.Wei, D.Brooks, A.Tumeo, G.Gopalakrishnan A.Li: "ASAP - Automatic Synthesis of Area-Efficient and  Precision-Aware CGRA", the 36th ACM International Conference on Supercomputing.

​​

   2021:

• [MICRO 2021] T.Geng, C.Wu, ..., M.Herbordt, Y.Lin, A.Li: "I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization", the 54th IEEE/ACM International Symposium on Microarchitecture.

• [TPDS 2021] T.Geng, T.Wang, C.Wu, Y.Li, ..., A.Li, M.Herbordt: "O3BNN-R: An Out-Of-Order Architecture for HighPerformance and Regularized BNN inference", IEEE Transactions on Parallel and Distributed Systems.

• [TPDS 2021] C.Tan, C.Xie, T.Geng, ..., K.Barker, A.Li: "ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing", IEEE Transactions on Parallel and Distributed Systems.

• [SC 2021] B.Feng, Y.Wang, T.Geng, A.Li, Y.Ding: "APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores", Proceedings of the International Conference for High-Performance Computing, Networking, Storage, and Analysis.

• [ICCAD 2021] Y.Zhang, H.You, Y.Fu, T.Geng, A.Li, Y.Lin: "G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency", 2021 International Conference On Computer Aided Design.

• [ICCD 2021] C.Tan, T.Geng, C.Xie, N.Agostini, J.Li, A.Li, K.Barker, A.Tumeo: "DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications", the 39th IEEE International Conference on Computer Design. (Best Paper Award)

​​

   2020:

• [MICRO 2020] T.Geng, A.Li, T.Wang, C.Wu, Y.Li, ..., M.Herbordt: "AWB-GCN: A Hardware Accelerator of GraphConvolution-Network through Runtime Workload Rebalancing", the 53rd IEEE/ACM International Symposium on Microarchitecture.

• [TC 2020] T.Geng*, T.Wang*, A.Li, X.Jin, M.Herbordt: "FPDeep: Scalable Acceleration of CNN Training on DeeplyPipelined FPGA Clusters", IEEE Transactions on Computers. 

• [ICS 2020] T.Geng*, R.Shi*, P.Dong*, ..., M.Herbordt, A.Li, Y.Wang: "CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks", the 34th ACM International Conference on Supercomputing.

​​

   2019:

• [ICS 2019] T.Geng, T.Wang, C.Wu, C.Yang, W.Wu, A.Li, M.Herbordt: "O3BNN: An Out-Of-Order Architecture for High-Performance Binarized Neural Network Inference with Fine-Grained Pruning", the 33th ACM International Conference on Supercomputing.

• [SC 2019] A.Li, T.Geng, T.Wang, M.Herbordt, S.Song, K.Barker: "BSTC: A Novel BinarizedSoft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets", Proceedings of the International Conference for High-Performance Computing, Networking, Storage, and Analysis.

• [SC 2019] C.Yang, T.Geng, T.Wang, ..., M.Herbordt: "Fully integrated FPGA molecular dynamics simulations", Proceedings of the International Conference for High-Performance Computing, Networking, Storage, and Analysis.