Poster: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation. - Hang Liu 001; Jung Hee Seo; Rajat Mittal 002 (SC Companion, 2012)

Abstract: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation. - Hang Liu 001; Jung Hee Seo; Rajat Mittal 002; H. Howie Huang (SC Companion, 2012)

GPU-accelerated scalable solver for banded linear systems. - Hang Liu 001; Jung Hee Seo; Rajat Mittal 002; H. Howie Huang (CLUSTER, 2013)

Big data machine learning and graph analytics: Current state and future challenges. - H. Howie Huang; Hang Liu 001 (IEEE BigData, 2014)

Optimizing job reliability via contention-free, distributed scheduling of vm checkpointing. - Yu Xiang 003; Hang Liu 001; Tian Lan 001; H. Howie Huang; Suresh Subramaniam 001 (DCC@SIGCOMM, 2014)

Enterprise: breadth-first graph traversal on GPUs. - Hang Liu 001; H. Howie Huang (SC, 2015)

iBFS: Concurrent Breadth-First Search on GPUs. - Hang Liu 001; H. Howie Huang; Yang Hu (SIGMOD Conference, 2016)

Computational modeling of cardiac hemodynamics: Current status and future outlook. - Rajat Mittal 002; Jung Hee Seo; Vijay Vedula; Young J. Choi; Hang Liu 001; H. Howie Huang; Saurabh Jain; Laurent Younes; Theodore Abraham; Richard T. George (J. Comput. Phys., 2016)

Graphene: Fine-Grained IO Management for Graph Computing. - Hang Liu 001; H. Howie Huang (FAST, 2017)

Do Bitcoin Users Really Care About Anonymity? An Analysis of the Bitcoin Transaction Graph. - Anil Gaihre; Yan Luo 001; Hang Liu 001 (IEEE BigData, 2018)

UKSM: Swift Memory Deduplication via Hierarchical and Adaptive Memory Region Distilling. - Nai Xia; Chen Tian 001; Yan Luo 001; Hang Liu 001; Xiaoliang Wang 001 (FAST, 2018)

High-Performance Triangle Counting on GPUs. - Yang Hu; Hang Liu 001; H. Howie Huang (HPEC, 2018)

TriCore: parallel triangle counting on GPUs. - Yang Hu; Hang Liu 001; H. Howie Huang (SC, 2018)

iSpan: parallel identification of strongly connected components with spanning trees. - Yuede Ji; Hang Liu 001; H. Howie Huang (SC, 2018)

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks. - Linnan Wang; Wei Wu 016; Yiyang Zhao; Junyu Zhang; Hang Liu 001; George Bosilca; Jack J. Dongarra; Maurice Herlihy; Rodrigo Fonseca (CoRR, 2018)

Deanonymizing Cryptocurrency With Graph Learning: The Promises and Challenges. - Anil Gaihre; Santosh Pandey; Hang Liu 001 (CNS, 2019)

Dr. BFS: Data Centric Breadth-First Search on FPGAs. - Eric Finnerty; Zachary Sherer; Hang Liu 001; Yan Luo 001 (DAC, 2019)

Software Hardware Co-Optimized BFS on FPGAs. - Zachary Sherer; Eric Finnerty; Yan Luo 001; Hang Liu 001 (FPGA, 2019)

XBFS: eXploring Runtime Optimizations for Breadth-First Search on GPUs. - Anil Gaihre; Zhenlin Wu; Fan Yao; Hang Liu 001 (HPDC, 2019)

H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs. - Santosh Pandey; Xiaoye Sherry Li; Aydin Buluç; Jiejun Xu; Hang Liu 001 (HPEC, 2019)

CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching. - Bibek Bhattarai; Hang Liu 001; H. Howie Huang (SIGMOD Conference, 2019)

SIMD-X: Programming and Processing of Graph Algorithms on GPUs. - Hang Liu 001; H. Howie Huang (USENIX ATC, 2019)

Universal Location Referencing and Homomorphic Evaluation of Geospatial Query. - Asma Aloufi; Peizhao Hu; Hang Liu 001; Sherman S. M. Chow (IACR Cryptol. ePrint Arch., 2019)

FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. - Runbin Shi; Yuhao Ding; Xuechao Wei; He Li 008; Hang Liu 001; Hayden Kwok-Hay So; Caiwen Ding (DAC, 2020)

Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. - Bingbing Li; Zhenglun Kong; Tianyun Zhang; Ji Li 006; Zhengang Li; Hang Liu 001; Caiwen Ding (EMNLP (Findings), 2020)

FTDL: An FPGA-tailored Architecture for Deep Learning Systems. - Runbin Shi; Yuhao Ding; Xuechao Wei; Hang Liu 001; Hayden Kwok-Hay So; Caiwen Ding (FPGA, 2020)

SWARMGRAPH: Analyzing Large-Scale In-Memory Graphs on GPUs. - Yuede Ji; Hang Liu 001; H. Howie Huang (HPCC/DSS/SmartCity, 2020)

FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks. - Linnan Wang; Wei Wu 016; Junyu Zhang; Hang Liu 001; George Bosilca; Maurice Herlihy; Rodrigo Fonseca (HPDC, 2020)

BranchSpec: Information Leakage Attacks Exploiting Speculative Branch Instruction Executions. - Md Hafizul Islam Chowdhuryy; Hang Liu 001; Fan Yao (ICCD, 2020)

FTRANS: energy-efficient acceleration of transformers using FPGA. - Bingbing Li; Santosh Pandey; Haowen Fang; Yanjun Lyv; Ji Li 006; Jieyang Chen; Mimi Xie; Lipeng Wan 001; Hang Liu 001; Caiwen Ding (ISLPED, 2020)

ELDA: LDA made efficient via algorithm-system codesign submission. - Shilong Wang; Da Li; Hengyong Yu; Hang Liu 001 (PPoPP, 2020)

C-SAW: a framework for graph sampling and random walk on GPUs. - Santosh Pandey; Lingda Li; Adolfy Hoisie; Xiaoye S. Li; Hang Liu 001 (SC, 2020)

GSoFa: Scalable Sparse LU Symbolic Factorization on GPUs. - Anil Gaihre; Xiaoye S. Li; Hang Liu 001 (CoRR, 2020)

MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (CoRR, 2020)

SAPAG: A Self-Adaptive Privacy Attack From Gradients. - Yijue Wang; Jieren Deng; Dan Guo; Chenghong Wang; Xianrui Meng; Hang Liu 001; Caiwen Ding; Sanguthevar Rajasekaran (CoRR, 2020)

PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search. - Bolong Zheng; Xi Zhao 006; Lianggui Weng; Nguyen Quoc Viet Hung; Hang Liu 001; Christian S. Jensen (Proc. VLDB Endow., 2020)

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (ASAP, 2021)

TAG: Gradient Attack on Transformer-based Language Models. - Jieren Deng; Yijue Wang; Ji Li 006; Chenghong Wang; Chao Shang; Hang Liu 001; Sanguthevar Rajasekaran; Caiwen Ding (EMNLP (Findings), 2021)

Tahoe: tree structure-aware high performance inference engine for decision tree ensemble on GPU. - Zhen Xie; Wenqian Dong; Jiawen Liu; Hang Liu 001; Dong Li 001 (EuroSys, 2021)

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. - Shaoyi Huang; Shiyang Chen 004; Hongwu Peng; Daniel Manu; Zhenglun Kong; Geng Yuan; Lei Yang 018; Shusen Wang; Hang Liu 001; Caiwen Ding (ACM Great Lakes Symposium on VLSI, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (ICCAD, 2021)

Against Membership Inference Attack: Pruning is All You Need. - Yijue Wang; Chenghong Wang; Zigeng Wang; Shanglin Zhou; Hang Liu 001; Jinbo Bi; Caiwen Ding; Sanguthevar Rajasekaran (IJCAI, 2021)

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. - Geng Yuan; Payman Behnam; Zhengang Li; Ali Shafiee; Sheng Lin 001; Xiaolong Ma; Hang Liu 001; Xuehai Qian; Mahdi Nazm Bojnordi; Yanzhi Wang; Caiwen Ding (ISCA, 2021)

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. - Hongwu Peng; Shaoyi Huang; Tong Geng; Ang Li 006; Weiwen Jiang; Hang Liu 001; Shusen Wang; Caiwen Ding (ISQED, 2021)

E.T.: re-thinking self-attention for transformer models on GPUs. - Shiyang Chen 004; Shaoyi Huang; Santosh Pandey; Bingbing Li; Guang R. Gao; Long Zheng 001; Caiwen Ding; Hang Liu 001 (SC, 2021)

Dr. Top-k: delegate-centric Top-k on GPUs. - Anil Gaihre; Da Zheng; Scott Weitze; Lingda Li; Shuaiwen Leon Song; Caiwen Ding; Xiaoye S. Li; Hang Liu 001 (SC, 2021)

Universal location referencing and homomorphic evaluation of geospatial query. - Asma Aloufi; Peizhao Hu; Hang Liu 001; Sherman S. M. Chow; Kim-Kwang Raymond Choo (Comput. Secur., 2021)

TAG: Transformer Attack from Gradient. - Jieren Deng; Yijue Wang; Ji Li 006; Chao Shang; Hang Liu 001; Sanguthevar Rajasekaran; Caiwen Ding (CoRR, 2021)

SimNet: Computer Architecture Simulation using Machine Learning. - Lingda Li; Santosh Pandey; Thomas Flynn 001; Hang Liu 001; Noel Wheeler; Adolfy Hoisie (CoRR, 2021)

Binary Complex Neural Network Acceleration on FPGA. - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. - Shaoyi Huang; Dongkuan Xu; Ian En-Hsu Yen; Sung-En Chang; Bingbing Li; Shiyang Chen 004; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. - Bingbing Li; Hongwu Peng; Rajat Sainju; Junhuan Yang; Lei Yang 018; Yueying Liang; Weiwen Jiang; Binghui Wang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Optimizing Job Reliability Through Contention-Free, Distributed Checkpoint Scheduling. - Yu Xiang 003; Hang Liu 001; Tian Lan 001; H. Howie Huang; Suresh Subramaniam 001 (IEEE Trans. Netw. Serv. Manag., 2021)

Trust: Triangle Counting Reloaded on GPUs. - Santosh Pandey; Zhibin Wang 002; Sheng Zhong 002; Chen Tian 001; Bolong Zheng; Xiaoye S. Li; Lingda Li; Adolfy Hoisie; Caiwen Ding; Dong Li 001; Hang Liu 001 (IEEE Trans. Parallel Distributed Syst., 2021)

T-GCN: A Sampling Based Streaming Graph Neural Network System with Hybrid Architecture. - Chengying Huan; Shuaiwen Leon Song; Yongchao Liu; Heng Zhang 005; Hang Liu 001; Charles He; Kang Chen; Jinlei Jiang; Yongwei Wu 001 (PACT, 2022)

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. - Shaoyi Huang; Dongkuan Xu; Ian En-Hsu Yen; Yijue Wang; Sung-En Chang; Bingbing Li; Shiyang Chen 004; Mimi Xie; Sanguthevar Rajasekaran; Hang Liu 001; Caiwen Ding (ACL (1), 2022)

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. - Hongwu Peng; Shaoyi Huang; Shiyang Chen 004; Bingbing Li; Tong Geng; Ang Li 006; Weiwen Jiang; Wujie Wen; Jinbo Bi; Hang Liu 001; Caiwen Ding (DAC, 2022)

TeGraph: A Novel General-Purpose Temporal Graph Computing Engine. - Chengying Huan; Hang Liu 001; Mengxing Liu; Yongchao Liu; Changhua He; Kang Chen; Jinlei Jiang; Yongwei Wu 001; Shuaiwen Leon Song (ICDE, 2022)

Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems. - Heng Zhang 005; Lingda Li; Hang Liu 001; Donglin Zhuang; Rui Liu 002; Chengying Huan; Shuang Song; Dingwen Tao; Yongchao Liu; Charles He; Yanjun Wu; Shuaiwen Leon Song (ICS, 2022)

Variance of the Gradient Also Matters: Privacy Leakage from Gradients. - Yijue Wang; Jieren Deng; Dan Guo; Chenghong Wang; Xianrui Meng; Hang Liu 001; Chao Shang; Binghui Wang; Qin Cao; Caiwen Ding; Sanguthevar Rajasekaran (IJCNN, 2022)

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs. - Santosh Pandey; Lingda Li; Thomas Flynn 001; Adolfy Hoisie; Hang Liu 001 (SC, 2022)

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning. - Lingda Li; Santosh Pandey; Thomas Flynn 001; Hang Liu 001; Noel Wheeler; Adolfy Hoisie (Proc. ACM Meas. Anal. Comput. Syst., 2022)

iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees. - Yuede Ji; Hang Liu 001; Yang Hu; H. Howie Huang (ACM Trans. Parallel Comput., 2022)

gSoFa: Scalable Sparse Symbolic LU Factorization on GPUs. - Anil Gaihre; Xiaoye Sherry Li; Hang Liu 001 (IEEE Trans. Parallel Distributed Syst., 2022)

PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search. - Bolong Zheng; Xi Zhao 006; Lianggui Weng; Quoc Viet Hung Nguyen; Hang Liu 001; Christian S. Jensen (VLDB J., 2022)

TEA: A General-Purpose Temporal Graph Random Walk Engine. - Chengying Huan; Shuaiwen Leon Song; Santosh Pandey; Hang Liu 001; Yongchao Liu; Baptiste Lepers; Changhua He; Kang Chen; Jinlei Jiang; Yongwei Wu 001 (EuroSys, 2023)

Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. - Andy Trinh; Shivam Sheth; Anil Gaihre; Caiwen Ding; Jieyang Chen; Feiyi Wang; David Pugmire; Scott Klasky; Hang Liu 001; Lipeng Wan 001 (HPCC/DSS/SmartCity/DependSys, 2023)

TANGO: re-thinking quantization for graph neural network training on GPUs. - Shiyang Chen 004; Da Zheng; Caiwen Ding; Chengying Huan; Yuede Ji; Hang Liu 001 (SC, 2023)

PeeK: A Prune-Centric Approach for K Shortest Path Computation. - Wang Feng; Shiyang Chen 004; Hang Liu 001; Yuede Ji (SC, 2023)

ezLDA: Efficient and Scalable LDA on GPUs. - Shilong Wang; Hang Liu 001; Anil Gaihre; Hengyong Yu (IEEE Access, 2023)

Tango: rethinking quantization for graph neural network training on GPUs. - Shiyang Chen 004; Da Zheng; Caiwen Ding; Chengying Huan; Yuede Ji; Hang Liu 001 (CoRR, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Motif-Based Graph Representation Learning with Application to Chemical Molecules. - Yifei Wang 002; Shiyang Chen 004; Guobin Chen; Ethan Shurberg; Hang Liu 001; Pengyu Hong (Informatics, 2023)

Establish the basis for Breadth-First Search on Frontier System: XBFS on AMD GPUs. - Haoshen Yang; Hao Lu 001; Naw Safrin Sattar; Hang Liu 001; Feiyi Wang (SC Workshops, 2024)

Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. - Bingbing Li; Geng Yuan; Zigeng Wang; Shaoyi Huang; Hongwu Peng; Payman Behnam; Wujie Wen; Hang Liu 001; Caiwen Ding (CoRR, 2024)

TAO: Re-Thinking DL-based Microarchitecture Simulation. - Santosh Pandey; Amir Yazdanbakhsh; Hang Liu 001 (Proc. ACM Meas. Anal. Comput. Syst., 2024)

TEA+: A Novel Temporal Graph Random Walk Engine with Hybrid Storage Architecture. - Chengying Huan; Yongchao Liu; Heng Zhang 005; Shuaiwen Song; Santosh Pandey; Shiyang Chen 004; Xiangfei Fang; Yue Jin; Baptiste Lepers; Yanjun Wu; Hang Liu 001 (ACM Trans. Archit. Code Optim., 2024)

TeGraph+: Scalable Temporal Graph Processing Enabling Flexible Edge Modifications. - Chengying Huan; Yongchao Liu; Heng Zhang 005; Hang Liu 001; Shiyang Chen 004; Shuaiwen Leon Song; Yanjun Wu (IEEE Trans. Parallel Distributed Syst., 2024)

Bingo: Radix-based Bias Factorization for Random Walk on Dynamic Graphs. - Pinhuan Wang; Chengying Huan; Zhibin Wang 002; Chen Tian 001; Yuede Ji; Hang Liu 001 (EuroSys, 2025)

Swift Unfolding of Communities: GPU-Accelerated Louvain Algorithm. - Zhibin Wang 002; Xi Lin; Xue Li 024; Pinhuan Wang; Ziheng Meng; Hang Liu 001; Chen Tian 001; Sheng Zhong 002 (PPoPP, 2025)

KVDirect: Distributed Disaggregated LLM Inference. - Shiyang Chen 004; Rain Jiang; Dezhi Yu; Jinlai Xu; Mengyuan Chao; Fanlong Meng; Chenyu Jiang; Wei Xu; Hang Liu 001 (CoRR, 2025)

Deal: Distributed End-to-End GNN Inference for All Nodes. - Shiyang Chen 004; Xiang Song; Vasiloudis Theodore; Hang Liu 001 (CoRR, 2025)