Hang Liu

Orcid: 0000-0001-6323-7388

Affiliations:
  • Stevens Institute of Technology, HPDA lab, Hoboken, NJ, USA
  • University of Massachusetts Lowell, MA, USA (former)
  • George Washington University, Washington, DC, USA (former, PhD 2017)


According to our database1, Hang Liu authored at least 69 papers between 2012 and 2024.

Collaborative distances:

Timeline

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Bibliography

2024
Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM.
CoRR, 2024

2023
Motif-Based Graph Representation Learning with Application to Chemical Molecules.
Informatics, March, 2023

ezLDA: Efficient and Scalable LDA on GPUs.
IEEE Access, 2023

PeeK: A Prune-Centric Approach for K Shortest Path Computation.
Proceedings of the International Conference for High Performance Computing, 2023

TANGO: re-thinking quantization for graph neural network training on GPUs.
Proceedings of the International Conference for High Performance Computing, 2023

Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics.
Proceedings of the IEEE International Conference on High Performance Computing & Communications, 2023

TEA: A General-Purpose Temporal Graph Random Walk Engine.
Proceedings of the Eighteenth European Conference on Computer Systems, 2023

2022
PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search.
VLDB J., 2022

gSoFa: Scalable Sparse Symbolic LU Factorization on GPUs.
IEEE Trans. Parallel Distributed Syst., 2022

iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees.
ACM Trans. Parallel Comput., 2022

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning.
Proc. ACM Meas. Anal. Comput. Syst., 2022

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs.
Proceedings of the SC22: International Conference for High Performance Computing, 2022

Variance of the Gradient Also Matters: Privacy Leakage from Gradients.
Proceedings of the International Joint Conference on Neural Networks, 2022

Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems.
Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

TeGraph: A Novel General-Purpose Temporal Graph Computing Engine.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

T-GCN: A Sampling Based Streaming Graph Neural Network System with Hybrid Architecture.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

2021
Trust: Triangle Counting Reloaded on GPUs.
IEEE Trans. Parallel Distributed Syst., 2021

Optimizing Job Reliability Through Contention-Free, Distributed Checkpoint Scheduling.
IEEE Trans. Netw. Serv. Manag., 2021

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT.
CoRR, 2021

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.
CoRR, 2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search.
CoRR, 2021

Binary Complex Neural Network Acceleration on FPGA.
CoRR, 2021

SimNet: Computer Architecture Simulation using Machine Learning.
CoRR, 2021

TAG: Transformer Attack from Gradient.
CoRR, 2021

Universal location referencing and homomorphic evaluation of geospatial query.
Comput. Secur., 2021

Dr. Top-k: delegate-centric Top-k on GPUs.
Proceedings of the International Conference for High Performance Computing, 2021

E.T.: re-thinking self-attention for transformer models on GPUs.
Proceedings of the International Conference for High Performance Computing, 2021

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator.
Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021

Against Membership Inference Attack: Pruning is All You Need.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper).
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU.
Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Tahoe: tree structure-aware high performance inference engine for decision tree ensemble on GPU.
Proceedings of the EuroSys '21: Sixteenth European Conference on Computer Systems, 2021

TAG: Gradient Attack on Transformer-based Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper).
Proceedings of the 32nd IEEE International Conference on Application-specific Systems, 2021

2020
PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search.
Proc. VLDB Endow., 2020

SAPAG: A Self-Adaptive Privacy Attack From Gradients.
CoRR, 2020

MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks.
CoRR, 2020

C-SAW: a framework for graph sampling and random walk on GPUs.
Proceedings of the International Conference for High Performance Computing, 2020

ELDA: LDA made efficient via algorithm-system codesign submission.
Proceedings of the PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020

FTRANS: energy-efficient acceleration of transformers using FPGA.
Proceedings of the ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design, 2020

BranchSpec: Information Leakage Attacks Exploiting Speculative Branch Instruction Executions.
Proceedings of the 38th IEEE International Conference on Computer Design, 2020

FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Networks.
Proceedings of the HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

SWARMGRAPH: Analyzing Large-Scale In-Memory Graphs on GPUs.
Proceedings of the 22nd IEEE International Conference on High Performance Computing and Communications; 18th IEEE International Conference on Smart City; 6th IEEE International Conference on Data Science and Systems, 2020

FTDL: An FPGA-tailored Architecture for Deep Learning Systems.
Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019
Universal Location Referencing and Homomorphic Evaluation of Geospatial Query.
IACR Cryptol. ePrint Arch., 2019

SIMD-X: Programming and Processing of Graph Algorithms on GPUs.
Proceedings of the 2019 USENIX Annual Technical Conference, 2019

CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching.
Proceedings of the 2019 International Conference on Management of Data, 2019

XBFS: eXploring Runtime Optimizations for Breadth-First Search on GPUs.
Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, 2019

Software Hardware Co-Optimized BFS on FPGAs.
Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

Dr. BFS: Data Centric Breadth-First Search on FPGAs.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks.
CoRR, 2018

iSpan: parallel identification of strongly connected components with spanning trees.
Proceedings of the International Conference for High Performance Computing, 2018

TriCore: parallel triangle counting on GPUs.
Proceedings of the International Conference for High Performance Computing, 2018

High-Performance Triangle Counting on GPUs.
Proceedings of the 2018 IEEE High Performance Extreme Computing Conference, 2018

UKSM: Swift Memory Deduplication via Hierarchical and Adaptive Memory Region Distilling.
Proceedings of the 16th USENIX Conference on File and Storage Technologies, 2018

2017
Graphene: Fine-Grained IO Management for Graph Computing.
Proceedings of the 15th USENIX Conference on File and Storage Technologies, 2017

2016
Computational modeling of cardiac hemodynamics: Current status and future outlook.
J. Comput. Phys., 2016

iBFS: Concurrent Breadth-First Search on GPUs.
Proceedings of the 2016 International Conference on Management of Data, 2016

2015
Enterprise: breadth-first graph traversal on GPUs.
Proceedings of the International Conference for High Performance Computing, 2015

2014
Optimizing job reliability via contention-free, distributed scheduling of vm checkpointing.
Proceedings of the 2014 ACM SIGCOMM workshop on Distributed cloud computing, 2014

Big data machine learning and graph analytics: Current state and future challenges.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
GPU-accelerated scalable solver for banded linear systems.
Proceedings of the 2013 IEEE International Conference on Cluster Computing, 2013

2012
Abstract: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Poster: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012


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