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Tony Geng

Assistant Professor

Department of ECE

Department of Computer Science

University of Rochester

tong.geng(at)rochester.edu

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HELLO, I'M

Tony Geng

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Assistant Professor @ University of Rochester

About

About Tony

MY BACKGROUND

Dr. Tony Geng is a tenure-track assistant professor in the ECE and CS departments of the University of Rochester (UR) and the director of UR's IntelliArch Lab. He also holds secondary appointments with the Goergen Institute for Data Science. Before joining Rochester, Tony worked in the Physical & Computational Sciences Directorate (PCSD) at Pacific Northwest National Laboratory (PNNL) operated by the Department of Energy of the US government. His research interests are at the intersection of Computer Architecture & Systems, Generative AI, Graph Intelligence, and High-Performance Computing. Tony's papers have appeared in many prestigious conferences and journals e.g. ISCA, MICRO, HPCA, OSDI, ICLR, ICML, NIPS, CVPR, ICCV, AAAI, DAC, SC, TPDS, TC, and TIP.

To prospective students:

I am currently looking for two Ph.D. students and one PostDoc to work on next-generation hardware architectures & systems for future Generative AI, graph intelligence, and their applications. Please drop me an email with your CV and transcripts if you are interested.

RESEARCH INTERESTS

Computer Architecture: GPU, FPGA, CGRA, Accelerators for AI, Nature-Powered Computer

Machine Learning: Generative AI,  Graph Learning, Nature-Powered ML

Applications: Fintech, Social Media, Recommendation System, Plasma Physics, Power Grid
publicaton

Selected Publications

​   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 51th IEEE/ACM International Symposium on Computer Architecture.

  • [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.

  • [ICML 2024] C.Han, Y.Lu, ..., R.Rao, T.Geng, Z.Tao, D.Liu: "Prototypical Transformer As Unified Motion Learners", Forty-first 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.

  • [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:

  • [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.

  • [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.

  • [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).

  • [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.

  • [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.

  • [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.

  • [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.

  • [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.

  • [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.

  • [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.

  • [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.

Projects

Projects

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Graph

Learning

Generative AI

Computer

Architecture

 View Selected Papers for More Details:

MICRO 20, MICRO 21, HPCA 21AAAI 23, DAC 23, OSDI 23, MICRO 23, NIPS 23, ISCA 24, ICLR 24

 View Selected Papers for More Details:

SC 19, ICS 19, TC 20, ICS 20, SC 21, TPDS 21,  DAC22, TIP 23, CVPR 23, TPDS 22, DAC 23, NIPS 23, ICCV 23, ICML 24

 View Selected Papers for More Details:

 

SC19, MICRO 20, MICRO 21, HPCA 21, ICCD 21, TPDS2021, ICS 22, DAC 23, ICS 23, MICRO 23, ICS 24 

Team

Meet The Team

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Chunshu Wu 

Research Interests:

1. Dynamical System for ML;

2. Computer Architecture;

3. AI for Science;

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Pouya Haghi

Research Interests:

1. Heterogeneous System for AI

2. Efficient Diffusion Models 

3. Efficient Large Language Models

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Clein Song

Research Interests:

1. Computer Architecture

2. Dynamical-System-based Compute Substrate

3. Generative AI Codesign

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Chuan Liu

Research Interests:

1. Graph Learning

2. Generative AI for Science

3. Dynamical-System-based Machine Learning

Awards & Services
News

News

06/2024 One paper accepted by SC 2024. 

06/2024 Prof. Tony Geng received Research Award from NERSC on GenAI -- providing 40000 GPU hours. 

05/2024 Pouya will join Meta in August as an AI chip architect with an unbelievable package. Big Congrats to Pouya!!! 

05/2024 Prof. Tony Geng received the Award for Excellence in Graduate Teaching!

05/2024 One paper accepted by ICML 2024. 

04/2024 One paper accepted by ICS 2024. 

03/2024 One paper accepted by ISCA 2024. 

01/2024 One paper accepted by TC 2024

01/2024 One paper accepted by ICLR 2024: Extending binary Ising machines to real-valued dynamical systems through hardware architecture and Hamiltonian codesign for graph learning problems. 

10/2023 Prof. Tony Geng received Research Fund from META Reality Lab on Next-generation Graphics Architecture.

09/2023 Two papers accepted by NIPS 2023.

08/2023 Prof. Tony Geng received Research Fund from NSF CORE program on GNN Acceleration based on Digital Hardware.

07/2023 Prof. Tony Geng received Research Fund from the New York State Center of Excellence in Data Science on Nature-powered Machine Learning.

07/2023 One paper accepted by MICRO 2023.

07/2023 One paper accepted by ICCAD 2023.

07/2023 One paper accepted by ICCV 2023.

07/2023 One paper accepted by JPCC (Journal of Physical Chemistry C) 2023.

06/2023 One paper accepted by SC 2023.

06/2023 Prof. Tony Geng received Donations from AMD and Xilinx, thanks!

04/2023 One paper accepted by IEEE Transactions on Image Processing (TIP) 2023 - Impact Factor: 10.86.

04/2023 Two papers accepted by ICS 2023 -- SmartNIC and SmartSwitch can significantly improve DLRM and GNN training efficiency.

03/2023 One paper accepted by OSDI 2023.

03/2023 Prof. Tony Geng received Research Fund from PNNL/DOE on Efficient Data Format for Large Language Model.

02/2023 One paper accepted by CVPR 2023 (as a Highlighted Paper).

02/2023 Three papers accepted by DAC 2023.

11/2022 One paper accepted by AAAI 2023.

10/2022 One paper accepted by TPDS 2022.

09/2022 Prof. Tony Geng received Faculty Research Award from META (Facebook) on AI System Hardware/Software Codesign.

09/2022 Our proposal was selected as an internationally excellent finalist in Meta (Facebook) RFP - Networking for AI.

09/2022 Four papers were accepted by ICCD 2022.06/2022 Three papers were accepted by FPL 2022.

04/2022 Two papers were accepted by ICS 2022.

02/2022 One paper was accepted by DAC 2022.

12/2021 Two papers were accepted by HPCA 2022.

Sponsors

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