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 hliu77@stevens.edu if you are interested!

News

• Jan 2022
  Welcome Runbang to join our group!
• Nov 2021
  TeGraph accepted to ICDE '22.
• June 2021
  Dr. Top-k and E.T. are accepted to SC '21, congratulations to all of us! Dr. Top-k can find top-k elements from a gigantic unsorted array lightning fast! and E.T. is faster than the state of the art enterprise solutions, such as, FasterTransformer and TensorRT! We will open source both projects very soon.
• May 2021
  GSoFa is accepted to TPDS, congratulations to Anil!
• May 2021
  I am honored to receive the 2021 ECE Outstanding Research Award! Thanks!
• April 2021
  My CPE 360 class receives top student evaluation score (3.94 out of 4)! Thank the students for this positive evaluation!
• 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!

Selected Publications

(Full publication list)

• [ICDE '22] TeGraph: A Novel General-Purpose Temporal Graph Computing Engine
• [SC '21] E.T.: Re-Thinking Self-Attention for Transformer Models on GPUs [Slides] [Source code]
• [SC '21] Dr.Top-k: Delegate-Centric Top-k Computation on GPUs [Slides] [Source code]
• [TPDS] GSOFA: Scalable Sparse Symbolic LU Factorization on GPUs
• [IJCAI '21] Against Membership Inference Attack: Pruning is All You Need
• [ISCA '21] FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
• [TPDS] TRUST: Triangle Counting Reloaded on GPUs [Source code]
• [Eurosys '21] Tahoe: Tree Structure-Aware High Performance Inference Engine for Decision Tree Ensemble on GPU
• [SC '20] C-SAW: A Framework for Graph Sampling and Random Walk on GPUs [Source code]
• [EMNLP Findings '20] Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
  
• [HPDC '20] FFT-based Gradient Sparsification for the Distributed Training of Deep Neural Network
• [DAC '20] FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability
• [VLDB '20] PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search [One of the best papers in VLDB '20]
  
• [GraphChallenge '19] H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs [Awarded Champion]
  
• [HPDC '19] XBFS: eXploring Dynamic Optimizations for Breadth-First Search on GPUs [Source code]
• [USENIX ATC '19] SIMD-X: Programming and Processing of Graph Algorithms on GPUs [Source code] [Video]
• [DAC '19] Dr. BFS: Data Centric Breadth-First Search on FPGAs
• [SIGMOD '19] CECI: Compact Embedding Cluster Indexfor Scalable Subgraph Matching
• [SC '18] TriCore: Parallel Triangle Counting on GPUs
• [SC '18] iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees
• [USENIX FAST '18] UKSM: Swift Memory Deduplication via Hierarchical and Adaptive Memory Region Distilling
• [USENIX FAST '17] Graphene: Fine-Grained IO Management for Graph Computing
• [Journal of Computational Physics '16] Computational Modeling of Cardiac Hemodynamics: Current Status and Future Outlook
• [SIGMOD '16] iBFS: Concurrent Breadth-First Search on GPUs
• [SC '15] Enterprise: Breadth-First Graph Traversal on GPUs

Students

I am very fortunate to work with the following people:

• PhD students
  • Anil Gaihre (Tribhuvan University, Nepal; SC, HPDC, TPDS, IEEE BigData)
  • Santosh Pandey (Tribhuvan University, Nepal; SC, TPDS)
  • Shiyang Chen (Huazhong University of Science and Technology, China; SC)
  • Zhanfu Yang(BS: Sun Yet-Sen University, China; MS: Purdue University)
  • Runbang Hu(Tsinghua University, China)
• Masters students
  • Scott Weitze
  • Luca Pasquariello
  • Yufeng Liu
  • Zehui Xie
• Undergraduate students
  • Pridhvi Myneni
  • Chris Waldt
  • Jared Kantor
  • Yohanes Gunarso
  • Daniel Giger
• Alumni
  • Shilong Wang (Ph.D., co-advised w/ Prof. Hengyong Yu). First employment: Cadence.
  • 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