Hang Liu

I am an Assistant Professor of Electrical and Computer Engineering at Stevens Institute of Technology, where I lead the HPDA lab. My research exploits emerging hardware — such as Graphics Processing Unit (GPU), Field-Programmable Gate Array (FPGA), high-end CPU and Solid-State Drive (SSD) — to build high-performance systems for graph computing, machine learning, computational omics, numerical simulation and cloud computing. I have received the NSF CRII and CAREER awards. Thanks NSF!

Prior to joining Stevens, I was an assistant professor at the University of Massachusetts Lowell. I received the Ph.D. degree from the George Washington University in 2017 (advisor: Prof. H. Howie Huang), and B.E. from Huazhong University of Science and Technology in 2011.

Some simple and actionable research advice: here [GitHub link].

I’m looking for motivated graduate students and undergraduate interns. Please contact me at Hang.Liu@stevens.edu if you are interested!

News

• Mar 2021
  Our group is selected to visit Lawrence Berkeley National Lab in the summer! Thanks SRP and our host Dr. Xiaoye S. Li.
• Feb 2021
  TRUST is accepted to IEEE Transactions on Parallel and Distributed Systems (TPDS)! Congrats Santosh and Zhibin! TRUST achieves unprecedentedly 1 trillion TEPS performance rate with 1,024 GPUs! Check it out here.
• Feb 2021
  I am also sharing my experience about NSF CAREER proposal writing at here [GitHub link]. Hope it will help you!
• Feb 2021
  My NSF CAREER Award has been funded! Thanks NSF!
• Jan 2021
  One paper accepted to Eurosys'21!
• Jan 2021
  Welcome Zhanfu to join our group!
• Oct 2020
  One paper accepted to IEEE Transactions on Network and Service Management!
• Oct 2020
  One paper accepted to HPCC '20!
• Sept 2020
  One paper accepted to ICCD '20!
• Sept 2020
  One paper accepted to EMNLP '20!
• Sept 2020
  Invited to serve as a PC member in IPDPS'21! Please submit your best work!
• Sept 2020
  Invited to serve as a PC member at algorithm track in SC'21! Please submit your best work!
• Sept 2020
  PM-LSH is selected as one of the best papers in VLDB'20!
• June 2020
  C-SAW is accepted to SC '20, congrats Santosh.
• May 2020
  HPDA is hosting a seminar about Actionable Guidance for Junior Researchers at 10:30am Wednesday May 20, 2020. The video is here.
• April 2020
  One distributed deep learning work is accepted to HPDC '20.
• Feb 2020
  One FPGA accelerated deep learning work is accepted to DAC '20.
• Dec 2019
  One collaborative work, i.e., PM-LSH is accepted to VLDB '20.
• Nov 2019
  ELDA (short paper) is accepted to PPoPP'20, congrats Shilong!
• Oct 2019
  One FPGA accelerated CNN work (short paper) is accepted to FPGA'20.
• Sept 2019
  One paper is accepted to eduHPC@SC'19
• Aug 2019
  H-INDEX won the champion of 2019 GraphChallenge. Congrats Santosh!
• Aug 2019
  Our group has moved to Stevens. I will miss the great days at Lowell!
• July 2019
  One poster is accepted to ACM undergraduate competition, congrats Daniel!
• May 2019
  Our group is visiting Lawrence Berkeley National Lab.
• April 2019
  SIMD-X is accepted to USENIX ATC'19.
• Mar 2019
  XBFS is accepted to HPDC '19. Congrats Anil!

Recent Publications

(Full publication list)

• TRUST: Triangle Counting Reloaded on GPUs
  Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li and Hang Liu
  TPDS [Source code]
• Tahoe: Tree Structure-Aware High Performance Inference Engine for Decision Tree Ensemble on GPU
  Zhen Xie, Wenqian Dong, Jiawen Liu, Hang Liu and Dong Li
  Eurosys 2021
• C-SAW: A Framework for Graph Sampling and Random Walk on GPUs
  Santosh Pandey, Lingda Li, Adolfy Hoisie, Xiaoye S. Li and Hang Liu
  SC 2020 [Source code]
• Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
  Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, and Caiwen Ding
  EMNLP Findings 2020
• BranchSpec: Information Leakage Attacks Exploiting Speculative Branch Instruction Executions
  Md Hafizul Islam Chowdhuryy, Hang Liu and Fan Yao
  ICCD 2020
• FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Network
  Linnan Wang, Wei Wu, Junyu Zhang, Hang Liu, George Bosilca, Maurice Herlihy and Rodrigo Fonseca
  HPDC 2020
• FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability
  Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden So and Caiwen Ding
  DAC 2020
• PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search [One of the best papers in VLDB '20]
  Bolong Zheng, Xi Zhao, Lianggui Weng, Nguyen Quoc Viet Hung, Hang Liu and Christian S. Jensen
  VLDB 2020
• ELDA: Efficient LDA on GPUs (short paper)
  Shilong Wang, Da Li, Hengyong Yu and Hang Liu
  PPoPP 2020
• Actionable Guidance for Fresh HPC Researchers
  Hang Liu and Chunhua Liao
  eduHPC@SC '19
• H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs [Awarded Champion]
  Santosh Pandey, Xiaoye Li, Aydin Buluc, Jiejun Xu and Hang Liu
  GraphChallenge 2019
• An Efficient Parallel Algorithm for Dominator Detection (ACM Undergraduate Poster Competition)
  Daniel Giger and Hang Liu
  SC 2019
• Deanonymizing Cryptocurrency with Graph Learning: The Promises and Challenges
  Anil Gaihre, Santosh Pandey and Hang Liu
  Dlot@CNS 2019
• Efficient Encoding and Reconstruction of HPCDatasets for Checkpoint/Restart
  Jialing Zhang, Xiaoyan Zhuo, Aekyeung Moon, Hang Liu and Seung Woo Son
  MSST 2019
• XBFS: eXploring Dynamic Optimizations for Breadth-First Search on GPUs
  Anil Gaihre, Zhenlin Wu, Fan Yao and Hang Liu
  HPDC 2019 [Source code]
• SIMD-X: Programming and Processing of Graph Algorithms on GPUs
  Hang Liu and H. Howie Huang
  USENIX ATC 2019 [Source code] [Video]
• Dr. BFS: Data Centric Breadth-First Search on FPGAs
  Eric Finnerty, Zach Sherer, Yan Luo and Hang Liu
  DAC 2019
• CECI: Compact Embedding Cluster Indexfor Scalable Subgraph Matching
  Bibek Bhattarai, Hang Liu and H. Howie Huang
  SIGMOD 2019

Students

I am very fortunate to work with the following people:

• PhD students
  • Anil Gaihre
  • Santosh Pandey
  • Shilong Wang (co-advised with Hengyong Yu)
  • Shiyang Chen
  • Scott Weitze
  • Zhanfu Yang
• Masters students
  • Luca Pasquariello
  • Yufeng Liu
  • Zehui Xie
• Undergraduate students
  • Pridhvi Myneni
  • Chris Waldt
  • Jared Kantor
  • Yohanes Gunarso
  • Daniel Giger
• Alumni
  • Zhenlin Wu (MS)
  • Hans-Edward Hoene (BS)
  • Andy MacGregor (BS)
  • Noah Saffie (BS)
  • Zach Sherer (BS)
  • Eric Finnerty (BS)
  • Alexander Main (BS)
  • Femi Ogunseye (Middlesex High School)

Professional Service

• Program Committee:
  • 2021: SC, HPDC, IPDPS
  • 2020: SC, HPDC, ICDCS
  • 2019: HPDC, IEEE BigData, NAS, Chapel@PLDI
  • 2018: HPDC, IPDPS, NAS, ASPLOS shadow PC
  • 2017: Eurosys shadow PC
• Editorial board: Journal of BigData: Theory and Practice
• Journal reviewer: TPDS 2016, 2017, 2018, 2019, 2020; TC 2018, 2019
• NSF panel: 2018, 2019, 2020, 2021

Teaching

• CPE 517 Computer and Digital Systems Architecture (Fall 2019, Spring 2020, Spring 2021)
• CPE 360 Computational Data Structures & Algorithms (Fall 2020)
• EECE4810/5730 Operating Systems (Fall 2018)
• EECE 7110 High-Performance Computing on GPUs (Spring 2018, Spring 2019)

Research Advice