Hang Liu - RankMe

104 papers A* 6A 22B 4C 2Misc 1Journal 45Unranked 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Vulnerabilities in Partial TEE-Shielded LLM Inference with Precomputed Noise. CoRR Abhishek Saini, Haolin Jiang, Hang Liu
2025	J	`jnl`	A Comprehensive Survey of Subgraph Matching: [Experiments & Analysis]. Proc. ACM Manag. Data Haolin Jiang, Santosh Pandey, Hang Liu
2025	A	`conf`	Bingo: Radix-based Bias Factorization for Random Walk on Dynamic Graphs. EuroSys Pinhuan Wang, Chengying Huan, Zhibin Wang, Chen Tian, Yuede Ji, Hang Liu
2025	J	`jnl`	Bingo: Radix-based Bias Factorization for Random Walk on Dynamic Graphs. CoRR Pinhuan Wang, Chengying Huan, Zhibin Wang, Chen Tian, Yuede Ji, Hang Liu
2025	J	`jnl`	Deal: Distributed End-to-End GNN Inference for All Nodes. CoRR Shiyang Chen, Xiang Song, Vasiloudis Theodore, Hang Liu
2025	A	`conf`	Demystifying the Resilience of Large Language Model Inference: An End-to-End Perspective. SC Yu Sun, Zachary Coalson, Shiyang Chen, Hang Liu, Zhao Zhang, Sanghyun Hong, Bo Fang, Lishan Yang
2025	J	`jnl`	KVDirect: Distributed Disaggregated LLM Inference. CoRR Shiyang Chen, Rain Jiang, Dezhi Yu, Jinlai Xu, Mengyuan Chao, Fanlong Meng, Chenyu Jiang, Wei Xu, Hang Liu
2025	B	`conf`	Swift Unfolding of Communities: GPU-Accelerated Louvain Algorithm. PPoPP Zhibin Wang, Xi Lin, Xue Li, Pinhuan Wang, Ziheng Meng, Hang Liu, Chen Tian, Sheng Zhong
2024	—	`conf`	Establish the basis for Breadth-First Search on Frontier System: XBFS on AMD GPUs. SC Workshops Haoshen Yang, Hao Lu, Naw Safrin Sattar, Hang Liu, Feiyi Wang
2024	—	`conf`	TAO: Re-Thinking DL-based Microarchitecture Simulation. SIGMETRICS/Performance (Abstracts) Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024	J	`jnl`	TAO: Re-Thinking DL-based Microarchitecture Simulation. Proc. ACM Meas. Anal. Comput. Syst. Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024	J	`jnl`	Tao: Re-Thinking DL-based Microarchitecture Simulation. CoRR Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
2024	J	`jnl`	TeGraph+: Scalable Temporal Graph Processing Enabling Flexible Edge Modifications. IEEE Trans. Parallel Distributed Syst. Chengying Huan, Yongchao Liu, Heng Zhang, Hang Liu, Shiyang Chen, Shuaiwen Leon Song, Yanjun Wu
2024	J	`jnl`	Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	J	`jnl`	Motif-Based Graph Representation Learning with Application to Chemical Molecules. Informatics Yifei Wang, Shiyang Chen, Guobin Chen, Ethan Shurberg, Hang Liu, Pengyu Hong
2023	A	`conf`	PeeK: A Prune-Centric Approach for K Shortest Path Computation. SC Wang Feng, Shiyang Chen, Hang Liu, Yuede Ji
2023	A	`conf`	TANGO: re-thinking quantization for graph neural network training on GPUs. SC Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	A	`conf`	TEA: A General-Purpose Temporal Graph Random Walk Engine. EuroSys Chengying Huan, Shuaiwen Leon Song, Santosh Pandey, Hang Liu, Yongchao Liu, Baptiste Lepers, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu
2023	J	`jnl`	Tango: rethinking quantization for graph neural network training on GPUs. CoRR Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	—	`conf`	Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan
2023	J	`jnl`	ezLDA: Efficient and Scalable LDA on GPUs. IEEE Access Shilong Wang, Hang Liu, Anil Gaihre, Hengyong Yu
2022	J	`jnl`	A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
2022	A*	`conf`	A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
2022	A	`conf`	Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems. ICS Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song
2022	J	`jnl`	Motif-based Graph Representation Learning with Application to Chemical Molecules. CoRR Yifei Wang, Shiyang Chen, Guobin Chen, Ethan Shurberg, Hang Liu, Pengyu Hong
2022	J	`jnl`	PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search. VLDB J. Bolong Zheng, Xi Zhao, Lianggui Weng, Quoc Viet Hung Nguyen, Hang Liu, Christian S. Jensen
2022	A	`conf`	Scalable Deep Learning-Based Microarchitecture Simulation on GPUs. SC Santosh Pandey, Lingda Li, Thomas Flynn, Adolfy Hoisie, Hang Liu
2022	—	`conf`	SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning. SIGMETRICS (Abstracts) Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie
2022	J	`jnl`	SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning. Proc. ACM Meas. Anal. Comput. Syst. Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie
2022	—	`conf`	Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding
2022	B	`conf`	T-GCN: A Sampling Based Streaming Graph Neural Network System with Hybrid Architecture. PACT Chengying Huan, Shuaiwen Leon Song, Yongchao Liu, Heng Zhang, Hang Liu, Charles He, Kang Chen, Jinlei Jiang, Yongwei Wu
2022	A*	`conf`	TeGraph: A Novel General-Purpose Temporal Graph Computing Engine. ICDE Chengying Huan, Hang Liu, Mengxing Liu, Yongchao Liu, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu, Shuaiwen Leon Song
2022	B	`conf`	Variance of the Gradient Also Matters: Privacy Leakage from Gradients. IJCNN Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran
2022	J	`jnl`	gSoFa: Scalable Sparse Symbolic LU Factorization on GPUs. IEEE Trans. Parallel Distributed Syst. Anil Gaihre, Xiaoye Sherry Li, Hang Liu
2022	J	`jnl`	iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees. ACM Trans. Parallel Comput. Yuede Ji, Hang Liu, Yang Hu, H. Howie Huang
2021	—	`conf`	Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. ISQED Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding
2021	A*	`conf`	Against Membership Inference Attack: Pruning is All You Need. IJCAI Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran
2021	—	`conf`	Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). ASAP Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
2021	J	`jnl`	Binary Complex Neural Network Acceleration on FPGA. CoRR Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
2021	J	`jnl`	Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. CoRR Bingbing Li, Hongwu Peng, Rajat Sainju, Junhuan Yang, Lei Yang, Yueying Liang, Weiwen Jiang, Binghui Wang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A	`conf`	Dr. Top-k: delegate-centric Top-k on GPUs. SC Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A	`conf`	E.T.: re-thinking self-attention for transformer models on GPUs. SC Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu
2021	A*	`conf`	FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. ISCA Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding
2021	J	`jnl`	FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. CoRR Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding
2021	—	`conf`	HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding
2021	A	`conf`	Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). ICCAD Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. CoRR Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Optimizing Job Reliability Through Contention-Free, Distributed Checkpoint Scheduling. IEEE Trans. Netw. Serv. Manag. Yu Xiang, Hang Liu, Tian Lan, H. Howie Huang, Suresh Subramaniam
2021	J	`jnl`	PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search. CoRR Bolong Zheng, Xi Zhao, Lianggui Weng, Nguyen Quoc Viet Hung, Hang Liu, Christian S. Jensen
2021	J	`jnl`	SimNet: Computer Architecture Simulation using Machine Learning. CoRR Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie
2021	J	`jnl`	Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding
2021	—	`conf`	TAG: Gradient Attack on Transformer-based Language Models. EMNLP (Findings) Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding
2021	J	`jnl`	TAG: Transformer Attack from Gradient. CoRR Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding
2021	J	`jnl`	TRUST: Triangle Counting Reloaded on GPUs. CoRR Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu
2021	A	`conf`	Tahoe: tree structure-aware high performance inference engine for decision tree ensemble on GPU. EuroSys Zhen Xie, Wenqian Dong, Jiawen Liu, Hang Liu, Dong Li
2021	J	`jnl`	Trust: Triangle Counting Reloaded on GPUs. IEEE Trans. Parallel Distributed Syst. Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu
2021	J	`jnl`	Universal location referencing and homomorphic evaluation of geospatial query. Comput. Secur. Asma Aloufi, Peizhao Hu, Hang Liu, Sherman S. M. Chow, Kim-Kwang Raymond Choo
2020	C	`conf`	BranchSpec: Information Leakage Attacks Exploiting Speculative Branch Instruction Executions. ICCD Md Hafizul Islam Chowdhuryy, Hang Liu, Fan Yao
2020	J	`jnl`	C-SAW: A Framework for Graph Sampling and Random Walk on GPUs. CoRR Santosh Pandey, Lingda Li, Adolfy Hoisie, Xiaoye S. Li, Hang Liu
2020	A	`conf`	C-SAW: a framework for graph sampling and random walk on GPUs. SC Santosh Pandey, Lingda Li, Adolfy Hoisie, Xiaoye S. Li, Hang Liu
2020	B	`conf`	ELDA: LDA made efficient via algorithm-system codesign submission. PPoPP Shilong Wang, Da Li, Hengyong Yu, Hang Liu
2020	J	`jnl`	EZLDA: Efficient and Scalable LDA on GPUs. CoRR Shilong Wang, Hang Liu, Anil Gaihre, Hengyong Yu
2020	—	`conf`	Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. EMNLP (Findings) Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding
2020	J	`jnl`	Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. CoRR Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding
2020	A	`conf`	FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks. HPDC Linnan Wang, Wei Wu, Junyu Zhang, Hang Liu, George Bosilca, Maurice Herlihy, Rodrigo Fonseca
2020	A*	`conf`	FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. DAC Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2020	A	`conf`	FTDL: An FPGA-tailored Architecture for Deep Learning Systems. FPGA Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2020	J	`jnl`	FTRANS: Energy-Efficient Acceleration of Transformers using FPGA. CoRR Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding
2020	A	`conf`	FTRANS: energy-efficient acceleration of transformers using FPGA. ISLPED Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding
2020	J	`jnl`	GSoFa: Scalable Sparse LU Symbolic Factorization on GPUs. CoRR Anil Gaihre, Xiaoye S. Li, Hang Liu
2020	J	`jnl`	MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. CoRR Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran
2020	J	`jnl`	PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search. Proc. VLDB Endow. Bolong Zheng, Xi Zhao, Lianggui Weng, Nguyen Quoc Viet Hung, Hang Liu, Christian S. Jensen
2020	J	`jnl`	SAPAG: A Self-Adaptive Privacy Attack From Gradients. CoRR Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Caiwen Ding, Sanguthevar Rajasekaran
2020	—	`conf`	SWARMGRAPH: Analyzing Large-Scale In-Memory Graphs on GPUs. HPCC/DSS/SmartCity Yuede Ji, Hang Liu, H. Howie Huang
2019	—	`conf`	CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching. SIGMOD Conference Bibek Bhattarai, Hang Liu, H. Howie Huang
2019	—	`conf`	Deanonymizing Cryptocurrency With Graph Learning: The Promises and Challenges. CNS Anil Gaihre, Santosh Pandey, Hang Liu
2019	A*	`conf`	Dr. BFS: Data Centric Breadth-First Search on FPGAs. DAC Eric Finnerty, Zachary Sherer, Hang Liu, Yan Luo
2019	Misc	`conf`	Efficient Encoding and Reconstruction of HPC Datasets for Checkpoint/Restart. MSST Jialing Zhang, Xiaoyan Zhuo, Aekyeung Moon, Hang Liu, Seung Woo Son
2019	—	`conf`	H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs. HPEC Santosh Pandey, Xiaoye Sherry Li, Aydin Buluç, Jiejun Xu, Hang Liu
2019	—	`ch.`	Parallel Graph Processing. Encyclopedia of Big Data Technologies Da Yan, Hang Liu
2019	—	`conf`	SIMD-X: Programming and Processing of Graph Algorithms on GPUs. USENIX ATC Hang Liu, H. Howie Huang
2019	A	`conf`	Software Hardware Co-Optimized BFS on FPGAs. FPGA Zachary Sherer, Eric Finnerty, Yan Luo, Hang Liu
2019	J	`jnl`	Universal Location Referencing and Homomorphic Evaluation of Geospatial Query. IACR Cryptol. ePrint Arch. Asma Aloufi, Peizhao Hu, Hang Liu, Sherman S. M. Chow
2019	A	`conf`	XBFS: eXploring Runtime Optimizations for Breadth-First Search on GPUs. HPDC Anil Gaihre, Zhenlin Wu, Fan Yao, Hang Liu
2018	J	`jnl`	Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers. CoRR Hang Liu, Yufei Ding, Da Zheng, Seung Woo Son, Da Yan
2018	—	`conf`	Do Bitcoin Users Really Care About Anonymity? An Analysis of the Bitcoin Transaction Graph. IEEE BigData Anil Gaihre, Yan Luo, Hang Liu
2018	—	`conf`	High-Performance Triangle Counting on GPUs. HPEC Yang Hu, Hang Liu, H. Howie Huang
2018	J	`jnl`	SIMD-X: Programming and Processing of Graph Algorithms on GPUs. CoRR Hang Liu, H. Howie Huang
2018	J	`jnl`	SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks. CoRR Linnan Wang, Wei Wu, Yiyang Zhao, Junyu Zhang, Hang Liu, George Bosilca, Jack J. Dongarra, Maurice Herlihy, Rodrigo Fonseca
2018	A	`conf`	TriCore: parallel triangle counting on GPUs. SC Yang Hu, Hang Liu, H. Howie Huang
2018	A	`conf`	UKSM: Swift Memory Deduplication via Hierarchical and Adaptive Memory Region Distilling. FAST Nai Xia, Chen Tian, Yan Luo, Hang Liu, Xiaoliang Wang
2018	A	`conf`	iSpan: parallel identification of strongly connected components with spanning trees. SC Yuede Ji, Hang Liu, H. Howie Huang
2017	A	`conf`	Graphene: Fine-Grained IO Management for Graph Computing. FAST Hang Liu, H. Howie Huang
2017	—	`conf`	Understanding the impact of lossy compressions on IoT smart farm analytics. IEEE BigData Aekyeung Moon, Jaeyoung Kim, Jialing Zhang, Hang Liu, Seung Woo Son
2016	J	`jnl`	Computational modeling of cardiac hemodynamics: Current status and future outlook. J. Comput. Phys. Rajat Mittal, Jung Hee Seo, Vijay Vedula, Young J. Choi, Hang Liu, H. Howie Huang, Saurabh Jain, Laurent Younes, Theodore Abraham, Richard T. George
2016	—	`conf`	iBFS: Concurrent Breadth-First Search on GPUs. SIGMOD Conference Hang Liu, H. Howie Huang, Yang Hu
2015	A	`conf`	Enterprise: breadth-first graph traversal on GPUs. SC Hang Liu, H. Howie Huang
2014	—	`conf`	Big data machine learning and graph analytics: Current state and future challenges. IEEE BigData H. Howie Huang, Hang Liu
2014	—	`conf`	Optimizing job reliability via contention-free, distributed scheduling of vm checkpointing. DCC@SIGCOMM Yu Xiang, Hang Liu, Tian Lan, H. Howie Huang, Suresh Subramaniam
2013	C	`conf`	GPU-accelerated scalable solver for banded linear systems. CLUSTER Hang Liu, Jung Hee Seo, Rajat Mittal, H. Howie Huang
2012	—	`conf`	Abstract: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation. SC Companion Hang Liu, Jung Hee Seo, Rajat Mittal, H. Howie Huang
2012	—	`conf`	Poster: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation. SC Companion Hang Liu, Jung Hee Seo, Rajat Mittal