HELLO, I'M
Tony Geng
Assistant Professor @ University of Rochester
Tony Geng
Assistant Professor
Department of ECE
Department of Computer Science
University of Rochester
tong.geng(at)rochester.edu
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. 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 for 2 years. He received his Ph.D. in Computer Engineering at Boston University in 2020. His research interests are at the intersection of computer architecture & systems, machine learning, graph intelligence, and high-performance computing. Tony's papers have appeared in many prestigious conferences and journals including MICRO, HPCA, OSDI, AAAI, CVPR, DAC, SC, TPDS, TC, etc.
To prospective students:
I am always looking for Postdoc, Ph.D. students, and Interns (remote is acceptable) to work on next-generation hardware architectures & systems for AI, graph intelligence, ML, and their applications including Fintech, Recommendation systems, Social media, and Smart city. Please drop me an email with your CV and transcripts if you are interested.
RESEARCH INTERESTS
Computer Architecture: GPU, FPGA, CGRA, Accelerators for AI, Quantum Computer, Future Heterogeneity in Hardware and System
Machine Learning: Spatio-temporal Graph Neural Networks, Broadly-defined Graph Intelligence, DNNs
Applications: Fintech, Social Media, Recommendation System, Smart City, Public Health, Supply Chain
Selected Publications
2023:
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[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.
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[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.
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[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.
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[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.
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[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.
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[CVPR 2023] Y.Lu, Q.Wang, S.Ma, T.Geng, Y.Chen, H.Chen, D.Liu: "TransFlow: Transformer as Flow Learner", onference on Computer Vision and Pattern Recognition 2023.
2022:
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[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.
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[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.
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[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.
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[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.
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[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.
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[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:
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[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.
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[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.
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[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.
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[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.
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[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.
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[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:
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[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.
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[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:
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[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.
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[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.
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[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
Graph
Intelligence
View Selected Papers for More Details:
I-GCN [MICRO 21]
GCoD [HPCA 22]
AWB-GCN [MICRO 20]
Ising-Traffic [AAAI 23]
Ising-RecSys [DAC 23]
DNN Inference & Training
View Selected Papers for More Details:
FPDeep [TC 20]
O3BNN[TPDS 21,ICS 19]
Tensor-Core ANN[SC 21]
BSTC[SC 19]
PASNet[DAC 23]
CGRA
Architecture
View Selected Papers for More Details:
DRIPS[HPCA 21]
DynPaC[ICCD 21]
ASAP[ICS 22]
ML-CGRA[DAC 23]
GPU
Architecture
View Selected Papers for More Details:
AP-TC [SC2021],
BSTC [SC 2019]
Sparse TC[TPDS2022]
NLP: RNN & Transformer
Drug Discovery --
Molecular Dynamics
View Selected Papers for More Details:
Co-design Transformer [DAC 2022],
CSB-RNN [ICS 2020],
FPGA Transformer[ISQED 2021]
View Selected Papers for More Details:
FPGA-based MD
[ICCAD 2021], [SC 2019], [FCCM2021], [FCCM2022]
Future Heterogeneity in Hardware and Systems
View Selected Papers for More Details:
ARENA[TPDS2021],
In-NIC Data Compression[ICS2022],
Smart NIC [ FCCM 2022],
Meet The Team
Zhenyu Pan
Research Interests:
1. Ising Graph Learning;
2. Graph Neural Network;
3. Quantum-Aided GNN;
Zhuo Liu
Research Interests:
1. Ising Graph Learning;
2. Temporal Graph Learning
3. Graphical Model;
Banksy Luo
Research Interests:
1. EDA
2. Computer Vision
3. Deep Learning
Clein Song
Chuan Liu
Research Interests:
1. Graph Neural Networks
2. Future Graph Learning
Research Interests:
1. VLSI
2. Mixed-Signal IC
3. Future Learning System
News
02/2023 One paper accepted by OSDI 2023.
02/2023 One paper accepted by CVPR 2023 (as a Highlighted Paper).
02/2023 Three papers accepted by DAC 2023 -- Congrats to the leading authors, Zhuo and Bansky, for publishing in their first Ph.D. semester.
11/2022 One paper accepted by AAAI 2023 -- Congrats to the leading author, Zhenyu, for publishing in his first Ph.D. semester.
11/2022 One paper accepted by LoG 2023 -- Learning on Graphs (LoG) Conference -- a very decent new conference, strongly recommend
10/2022 One paper accepted by TPDS 2022.
09/2022 Prof. Tony Geng received Meta (Facebook) Faculty Research Award on AI System Hardware/Software Codesign.
09/2022 Four papers were accepted by ICCD 2022.
09/2022 Our proposal was selected as an internationally excellent finalist in Meta (Facebook) RFP - Networking for AI.
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.
02/2022 Tony gave an invited talk at Northwestern University.
02/2022 Tony gave an invited talk at the University of Rochester.