Author underlined: students advised at Georgia Tech
❤︎2024 Best Paper Award❤︎ from Sharc Lab: PDF (authors: all Sharc members)
2024
| C [ASPDAC] | Cong Hao Exploring and Exploiting Runtime Reconfigurable Floating Point Precision in Scientific Computing: a Case Study for Solving PDEs 30th Asia and South Pacific Design Automation Conference (ASP-DAC), 2025 [Paper] [Code] |
| C [MLCAD] | Stefan Abi-Karam, Rishov Sarkar, Allison Seigler, Sean Lowe, Zhigang Wei, Hanqiu Chen, Nanditha Rao, Lizy John, Aman Arora, Cong Hao HLSFactory: A Framework Empowering High-Level Synthesis Datasets for Machine Learning and Beyond ACM/IEEE International Symposium on Machine Learning for CAD (MLCAD), 2024 ★Best Paper Award★ [Paper] [Doc] [Code] |
| C [IISWC] | Yuchen Xia, Jiho Kim, Yuhan Chen, Haojie Ye, Souvik Kundu, Cong Hao, Nishil Talati Understanding The Performance and Estimating The Cost Of LLM Fine-Tuning IEEE International Symposium on Workload Characterization (IISWC), 2024 |
| C [ICCAD] | Hanqiu Chen, Xuebin Yao, Pradeep Subedi, Cong Hao Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2024 [Paper] [Code] |
| C [FCCM] | Rishov Sarkar, Rachel Paul, Cong Hao LightningSimV2: Faster and Scalable Simulation for High-Level Synthesis via Graph Compilation and Optimization The International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2024 [Paper] [Code] [slides] [Video] |
| C [DAC] | Hanqiu Chen, Yitu Wang, Vitorio Cargnini, Mohammadreza Soltaniyeh, Dongyang Li, Gongjin Sun, Pradeep Subedi, Andrew Chang, Yiran Chen, Cong Hao ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model Proceedings of IEEE/ACM Design Automation Conference (DAC), 2024 |
| C [MLSys] | Jianming Tong*, Jingtian Dang*, Anupam Golder, Cong Hao, Arijit Raychowdhury, Tushar Krishna SmartPAF: Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption The Seventh Conference on Machine Learning and Systems, (MLSys), May 2024 |
| J [TODAES] | Nan Wu, Yingjie Li, Hang Yang, Hanqiu Chen, Steve Dai, Cong Hao, Cunxi Yu, Yuan Xie Survey of machine learning for software-assisted hardware design verification: Past, present, and prospect ACM Transactions on Design Automation of Electronic Systems 29, no. 4 (2024): 1-42 |
2023
| J [JPLEA] | Afolabi Ige, Linhao Yang, Hang Yang, Jennifer Hasler, Cong Hao Analog System High-Level Synthesis for Energy-Efficient Reconfigurable Computing Journal of Low Power Electronics and Applications (JPLEA), 2023 |
| J [TRETS] | Jennifer Hasler, Cong Hao Programmable Analog System Benchmarks leading to Efficient Analog Computation Synthesis ACM Transactions on Reconfigurable Technology and Systems (TRETS), Sep. 2023 |
| C [ICCAD] | Stefan Abi-Karam, Rishov Sarkar, Dejia Xu, Zhiwen Fan, Zhangyang Wang, Cong Hao INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023 |
| C [ICCAD] | Rishov Sarkar, Hanxue Liang, Zhiwen Fan, Zhangyang Wang, Cong Hao Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023 [paper] [code] |
| C [ICCAD] | Hanqiu Chen, Hang Yang, Stephen BR Fitzmeyer, Cong Hao Rapid-INR: Storage Efficient CPU-free DNN Training Using Implicit Neural Representation IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023 Paper Code |
| C [DAC] | Nan Wu, Yingjie Li, Steve Dai, Cong Hao, Cunxi Yu, Yuan Xie Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks Proceedings of IEEE/ACM Design Automation Conference (DAC), 2023 ★Best Paper Award★ [paper] [code] |
| C [FPL] | Stefan Abi-Karam, Cong Hao GNNBuilder: An Automated Framework for Generic Graph Neural Network Accelerator Generation, Simulation, and Optimization The International Conference on Field-Programmable Logic and Applications (FPL), 2023 ★FPL Community Award★ [paper] [code] |
| C [FCCM] | Rishov Sarkar, Cong Hao LightningSim: Fast and Accurate Trace-Based Simulation for High-Level Synthesis The International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2023 ★Best Paper Runner-up★ [paper] [code] [slides] |
| C [FCCM] | Hanqiu Chen, Cong Hao DGNN-Booster: A Generic FPGA Accelerator Framework For Dynamic Graph Neural Network Inference The International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2023 [paper] [code] |
| C [ISQED] | Lakshmi Sathidevi, Abhinav Sharma, Nan Wu, Xun Jiao, Cong Hao PreAxC: Error Distribution Prediction for Approximate Computing Quality Control using Graph Neural Networks International Symposium on Quality Electronic Design (ISQED), 2023 |
| C [DATE] | Akshay Karkal Kamath, Stefan Abi-Karam, Ashwin Bhat, Cong Hao M5: Multi-modal Multi-Task Model Mapping on Multi-FPGA with Accelerator Configuration Search Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023 |
| C [HPCA] | Rishov Sarkar, Stefan Abi-Karam, Yuqi He, Lakshmi Sathidevi, Cong Hao FlowGNN: A Dataflow Architecture for Universal Graph Neural Network Inference via Multi-Queue Streaming IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2023 [code] [paper] |
2022
| C [IISWC] | Hanqiu Chen, Yihan Jiang, Yahya AlHinai, Eunjee Na, Cong Hao Bottleneck Analysis of Dynamic Graph Neural Network Inference on CPU and GPU IEEE International Symposium on Workload Characterization (IISWC), 2022 [code] [paper] |
| C [NeurIPS] | Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang M3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design Neural Information Processing Systems (NeurIPS), 2022 |
| C [NeurIPS] | Haoyu Peter Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li Unsupervised Learning for Combinatorial Optimization with Principled Objective Design Neural Information Processing Systems (NeurIPS), 2022 |
| C [ASP-DAC] | Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao Data-Model-Circuit Tri-design for Ultra-light Video Intelligence on Edge Devices IEEE Asia and South Pacific Design Automation Conference (ASP-DAC), 2022 |
| C [AICAS] | Zishen Wan, Ashwin Lele, Bo Yu, Shaoshan Liu, Yu Wang, Vijay Janapa Reddi, Cong Hao, Arijit Raychowdhury Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022 (Invited). [paper] |
| C [MICCAI] | Qing Lu, Xiaowei Xu, Shunjie Dong, Cong Hao, Lei Yang, Cheng Zhuo, Yiyu Shi RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022 |
| C [ASAP] | Hanqiu Chen, Cong Hao Mask-Net: A Hardware-efficient Object Detection Network with Masked Region Proposals IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2022 |
| C [ASAP] | Nan Wu, Jiwon Lee, Yuan Xie, Cong Hao LOSTIN: Logic Optimization via Spatio-Temporal Information with Hybrid Graph Models IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2022 ★Best Paper Nomination★ [paper] [code] |
| W [DOSSA] | Rishov Sarkar, Cong Hao. A Generic FPGA Accelerator Framework for Ultra-Fast GNN Inference |
| C [DAC] | Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing Proceedings of IEEE/ACM Design Automation Conference (DAC), 2022. [paper] [code] |
| C [DAC] | Xinyi Zhang, Cong Hao, Peipei Zhou, Alex Jones, Jingtong Hu H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication Awareness Proceedings of IEEE/ACM Design Automation Conference (DAC), 2022. [paper] |
| C [arXiv] | Stefan Abi-Karam*, Yuqi He*, Rishov Sarkar*, Lakshmi Sathidevi, Zihang Qiao, Cong Hao (*Equal contribution) GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration arXiv preprint, 2022 [paper] [code] |
| J [TCAD] | Nan Wu, Yuan Xie, Cong Hao IronMan-Pro: Multi-objective Design Space Exploration in HLS via Reinforcement Learning and Graph Neural Network based Modeling IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), June, 2022 [paper] [code] |
2021
| C [HPCA] | Hanchen Ye, Cong Hao, Jianyi Cheng, Hyunmin Jeong, Jack Huang, Stephen Neuendorffer, Deming Chen ScaleHLS: Scalable High-Level Synthesis through MLIR IEEE International Symposium on High Performance Computer Architecture (HPCA), 2022 [paper] [code] |
| C [NeurIPS] | Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen Generic Neural Architecture Search via Regression Neural Information Processing Systems, 2021, ★Spotlight★ [paper] [code] |
| C [ASAP] | Xinheng Liu, Yao Chen, Cong Hao, Ashutosh Dhar, Deming Chen WinoCNN: Kernel Sharing Winograd Systolic Array for Efficient Convolutional Neural Network Acceleration on FPGAs IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2021 |
| C [GLSVLSI] | Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao 3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration ACM Great Lakes Symposium on VLSI (GLSVLSI), 2021 (Invited). [paper] [talk] |
| C [GLSVLSI] | Nan Wu, Yuan Xie, Cong Hao IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning ACM Great Lakes Symposium on VLSI (GLSVLSI), 2021, ★Best Paper Award★ [paper] [talk] |
| C [AICAS] | Cong Hao, Deming Chen Software/Hardware Co-design for Multi-modal Multi-task Learning in Autonomous System IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021 (Invited). [paper] [talk] |
| J [D&T] | Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen Enabling Design Methodologies and Future Trends forEdge AI: Specialization and Co-design IEEE Design & Test, 2021 [paper] |
| C [DAC] | Lixiang Li, Yao Chen, Zacharie Zirnheld, Pan Li, Cong Hao MeLoPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank Proceedings of IEEE/ACM Design Automation Conference (DAC), 2021. [code] [paper] [talk] |
| C [ICLR] | Kaiqi Zhang, Cole Hawkins, Xiyuan Zhang, Cong Hao, Zheng Zhang On-FPGA training with ultra memory reduction: A low-precision tensor method ICLR Workshop on Hardware-Aware Efficient Training (HAET), 2021. [paper] |
| C [DATE] | Dongning Ma, Rahul Thapa, Xingjian Wang, Cong Hao, Xun Jiao Workload-Aware Approximate Computing Configuration IEEE/ACM Design, Automation & Test in Europe Conference (DATE), 2021. [paper] |
2020
| J [TC] | Cheng Gong, Ye Lu, Tao Li, Cong Hao, Deming Chen, Yao Chen VecQ: High Accuracy DNN Model Compression with Vectorized Weight Quantization IEEE Transactions of Computers, 2020 [paper] [code] |
| J [TCDS] | Jianwei Zheng, Chao Lu, Cong Hao, Deming Chen, Donghui Guo Improving the Generalization Ability of Deep Neural Networks for Cross-Domain Visual Recognition IEEE Transactions on Cognitive and Developmental Systems, 2020 |
| C [GLSVLSI] | Cong Hao, Chen Yao, Xiaofan Zhang, Yuhong Li, Jinjun Xiong, Wen-mei Hwu, Deming Chen Effective Algorithm-Accelerator Co-design for AI Solutions on Edge Devices Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI), 2020 |
| C [DAC] | Yuhong Li*, Cong Hao*, Xiaofan Zhang, Chen Yao, Jinjun Xiong, Wen-mei Hwu, Deming Chen EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions Proceedings of IEEE/ACM Design Automation Conference (DAC), 2020. [paper] [talk] |
| C [FPGA] | Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Zetong Guan, Yongan Zhang, Yue Wang, Deming Chen, Yingyan Lin AutoDNNchip: An Automated DNN Chip Generator through Compilation, Optimization, and Exploration Proceedings of ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA), 2020. |
| C [MLSys] | Xiaofan Zhang, Haoming Lu, Cong Hao, Jiachen Li, Bowen Cheng, Yuhong Li, Kyle Rupnow, Jinjun Xiong, Thomas Huang, Honghui Shi, Wen-mei Hwu, Deming Chen SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems The Conference on Machine Learning and Systems (SysML), 2020. [paper] [code] |
2019
| J [TED] | Zhao Yi, Cong Hao, and Takeshi Yoshimura Thermal and Wire length Optimization With TSV Assignment for 3D-IC IEEE Transactions on Electron Devices, 2019 |
| C [ICCAD] | Cong Hao, Yao Chen, Xinheng Liu, Atif Sarwari, Daryl Sew, Ashutosh Dhar, Bryan Wu, Dongdong Fu, Jinjun Xiong, Wen-mei Hwu, Junli Gu, Deming Chen NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2019. |
| C [DAC] | Cong Hao, Xiaofan Zhang, Yuhong Li, Sitao Huang, Jinjun Xiong, Kyle Rupnow, Wen-Mei Hwu, Deming Chen FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge Proceedings of IEEE/ACM Design Automation Conference (DAC), 2019. [paper] |
| C [SiPS] | Cong Hao, Atif Sarwari, Bryan Wu, Zhijie Jin, Junli Gu, Deming Chen A Hybrid GPU + FPGA System Design for Autonomous Driving Cars Proceedings of IEEE International Workshop on Signal Processing Systems (SiPS), 2019 (invited). |
| C [ISVLSI] | Yao Chen, Kai Zhang, Cheng Gong, Cong Hao, Xiaofan Zhang, Tao Li, and Deming Chen TDLA: An Open-source Deep Learning Accelerator for Ternarized DNN Models on Embedded FPGA Proceedings of IEEE Computer Society Annual Symposium on VLSI, 2019. |
| C [IJCNN] | Cheng Gong, Ye Lu, Cong Hao, Xiaofan Zhang, Tao Li, Deming Chen, and Yao Chen μL2Q: An Ultra-Low Loss Quantization Method for DNN Compression Proceedings of International Joint Conference on Neural Networks (IJCNN), 2019. |
| W [ICML] | Xiaofan Zhang, Cong Hao, Yuhong Li, Yao Chen, Jinjun Xiong, Wen-Mei Hwu, Deming Chen A Bi-Directional Co-Design Approach to Enable Deep Learning on IoT Devices Joint Workshop on On-Device Machine Learning Compact Deep Neural Network Representations, ICML, 2019, ★Best Poster Award★ |
| C [FPGA] | Yao Chen, Jiong He, Xiaofan Zhang, Cong Hao, and Deming Chen Cloud-DNN: An Open Framework for Mapping DNN Models to Cloud FPGAs Proceedings of ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA), 2019. |
Prior to 2019
| J [SJTU] | Ma Jiayi, Cong Hao, Kundong Wang Decomposing and Cluster Refinement Design Method for Application-Specific Network-on-Chips Journal of Shanghai Jiao Tong University (Science), 2018 |
J [TVLSI] | Wang Nan, Wei Zhong, Cong Hao, Song Chen, Takeshi Yoshimura, Yu Zhu Leakage-power-aware scheduling with dual-threshold voltage design IEEE Transactions on Very Large Scale Integration Systems, September 2016. |
| J [IEICE] | Nan Wang, Song Chen, Cong Hao, Haoran Zhang, Takeshi Yoshimura Leakage Power-Aware Scheduling in High-Level Synthesis IEICE Transactions on Fundamentals of Electronics, Communications, and Computer Sciences, 2014. |
| C [ICSICT] | Cong Hao, Deming Chen Deep Neural Network Model and FPGA Accelerator Co-design: Opportunities and Challenges Proceedings of IEEE International Conference on Solid-State and Integrated Circuit Technology (ICSICT),2018. |
C [PATMOS] | Yi Zhao, Cong Hao, Takeshi Yoshimura TSV Assignment of Thermal and Wire length Optimization for 3D-IC Routing 28th IEEE International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS), 2018 |
| C [CEEC] | Cong Hao, Takeshi Yoshimura Application of on-line machine learning in optimization algorithms: A case study for local search Computer Science and Electronic Engineering (CEEC), IEEE, 2017 |
| C [MWSCAS] | Yangyizhou Wang, Cong Hao, Takeshi Yoshimura A Particle Swarm Optimization and Branch and Bound Based Algorithm for Economical Smart Home Scheduling In 20th IEEE MWSCAS, 2017 |
| C [PATMOS] | Yuxin Qian, Cong Hao, Takeshi Yoshimura 3D-IC signal TSV assignment for thermal and wire length optimization 27th IEEE International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS), 2017 |
| C [ISOCC] | Jiayi Ma, Cong Hao, Takeshi Yoshimura Power-efficient Partitioning and Cluster Generation Design for Application-Specific Network-on-Chip In 13th IEEE ISOCC, 2016 |
| C [MWSCAS] | Hui Zhu, Cong Hao, Takeshi Yoshimura Thermal-Aware Floorplanning for NoC-Sprinting In 59th IEEE MWSCAS,2016 |
| C [MWSCAS] | Cong Hao, Takeshi Yoshimura Economical Smart Home Scheduling for Single and Multiple Users In 59th IEEE MWSCAS, 2016 |
| C [NEWCAS] | Cong Hao, Nan Ding, Takeshi Yoshimura An Efficient Algorithm for 3D-IC TSV Assignment In 14th IEEE NEWCAS,2016, Best Student Paper |
| W [WAPCO] | Cong Hao, Takeshi Yoshimura EACH: An Energy-Efficient High-Level Synthesis Framework for Approximate Computing In 2nd IEEE WAPCO, 2016 |
| C [ASICON] | Jian-Mo Ni, Qian Ai, Cong Hao, Takeshi Yoshimura, Nan Wang Primal-Dual Method based Simultaneous Functional Unit and Register Binding In 10th ASICON, 2015 |
| W [IWLS] | Cong Hao, Nan Wang, Jian-Mo Ni, Takeshi Yoshimura An Efficient Tabu Search Methodology for Port Assignment Problem in High-Level Synthesis In 24th IWLS, 2015 |
| C [ASICON] | Cong Hao, Jian-Mo Ni, Hui-Tong Wang, Takeshi Yoshimura Simultaneous Scheduling and Binding For Resource Usage and Interconnect Complexity Reduction in High-Level Synthesis In 11th IEEE ASICON, 2015, Best Student Paper |
| C [ASP-DAC] | Cong Hao, Song Chen, Takeshi Yoshimura Network simplex method based Multiple Voltage Scheduling in Power-efficient High-level synthesis In 18th IEEE ASP-DAC, 2013, IEICE VLD Excellent Student Award |
| C [ASICON] | Cong Hao, Nan Wang, Song Chen, Takeshi Yoshimura, Min-You Wu Interconnection Allocation between Functional Units and Registers in High-Level Synthesis In 10th IEEE ASICON, 2013, Best Student Paper |
| C [ASICON] | Wang Nan, Cong Hao, Nan Liu, Haoran Zhang, Takeshi Yoshimura Timing and Resource-Constrained Leakage Power-aware Scheduling in High-Level Synthesis In 10th IEEE ASICON, 2013, |
| C [ASQED] | Cong Hao, Haoran Zhang, Song Chen, Takeshi Yoshimura, Min-You Wu Port Assignment for Multiplexer and Interconnection Optimization In 5th IEEE ASQED, 2013 |
| C [ASICON] | Haoran Zhang, Cong Hao, Nan Wang, Song Chen, Takeshi Yoshimura Power and Resource-aware Scheduling with Multiple Voltages In 10th IEEE ASICON, 2013, Best Student Paper |
| C [VLSI-DAT] | Cong Hao, Song Chen, Takeshi Yoshimura Port Assignment for Interconnect Reduction in High-Level Synthesis In 19th IEEE VLSI-DAT, 2012, Best Paper Nomination |