Weifeng Liu







TICOH is the acronym for the project entitled "Taming Irregular Computations On Heterogeneous processors" and granted by the EU H2020 Marie Skłodowska-Curie actions (MSCA) Individual fellowships (IF). The individual research in liaison with the host organization Norwegian University of Science and Technology (NTNU) will last for two years (2017-2019).

Now more and more heterogeneous processors are equipping modern supercomputers. Unfortunately, despite the progress of hardware infrastructure, the utilization of heterogeneous computing is still relatively low in practice. The objective of the project TICOH is to address the issue of currently unsatisfactory utilization of heterogeneous computing for irregular problems such as graph and sparse matrix processing. Achieving this requires a multi-level approach for best practices that toward best performance for irregular computations on best hardware selection.

The fellow Weifeng Liu is working at NTNU to tackle the challenges.

Scientific Publications Supported by the Project

  • [j6] Junhong Liu, Xin He, Weifeng Liu, Guangming Tan. "Register-Aware Optimizations for Parallel Sparse Matrix-Matrix Multiplication". International Journal of Parallel Programming (IJPP).
    [PDF] [Slides] [DOI] [BibTex]

  • [j5] Jing Chen, Jianbin Fang, Weifeng Liu, Tao Tang, Canqun Yang. "clMF: A Fine-Grained and Portable Alternating Least Squares Algorithm for Parallel Matrix Factorization". Future Generation Computer Systems (FGCS). (This is the extended paper of the Parlearning '17 work).
    [PDF] [DOI] [BibTeX] [Source code (opencl)]

  • [c10] Ang Li, Weifeng Liu, Linnan Wang, Kevin Barker, Shuaiwen Leon Song. "Warp-Consolidation: A Novel Execution Model for GPUs". 32nd ACM International Conference on Supercomputing (ICS '18).
    [PDF] [Slides] [DOI] [BibTeX]

  • [c9] Xinliang Wang, Weifeng Liu, Wei Xue, Li Wu. "swSpTRSV: A Fast Sparse Triangular Solve with Sparse Level Tile Layout on Sunway Architectures". 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP '18).
    [PDF] [Slides] [DOI] [BibTeX] [Source code (athread)]

  • [p1] Junhong Liu, Xin He, Weifeng Liu, Guangming Tan. "Register-based Implementation of the Sparse General Matrix-matrix Multiplication on GPUs". 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP '18).
    [PDF] [Poster] [DOI] [BibTeX]

  • [j4] Huamin Ren, Nattiya Kanhabua, Andreas Møgelmose, Weifeng Liu, Kaustubh Kulkarni, Sergio Escalera, Xavier Baró, Thomas B. Moeslund. "Back-Dropout Transfer Learning for Action Recognition". IET Computer Vision (IET CV).
    [PDF] [DOI] [BibTeX]

  • [c8] Ang Li, Weifeng Liu, Mads R. B. Kristensen, Brian Vinter, Hao Wang, Kaixi Hou, Andres Marquez, Shuaiwen Leon Song. "Exploring and Analyzing the Real Impact of Modern On-Package Memory on HPC Scientific Kernels". 2017 International Conference for High Performance Computing, Networking, Storage and Analysis (SC '17). Nominated for best paper.
    [PDF] [Slides] [DOI] [BibTeX]

  • [j3] Weifeng Liu, Ang Li, Jonathan D. Hogg, Iain S. Duff, Brian Vinter. "Fast Synchronization-Free Algorithms for Parallel Sparse Triangular Solves with Multiple Right-Hand Sides". Concurrency and Computation: Practice and Experience (CCPE). (This is the extended paper of the Euro-Par '16 work).
    [PDF] [DOI] [BibTeX] [Source code (cuda, opencl-amd)]
    [This Sync-free algorithm is incorporated in the MAGMA main branch.]

  • [c7] Kaixi Hou, Weifeng Liu, Hao Wang, Wu-chun Feng. "Fast Segmented Sort on GPUs". 31st ACM International Conference on Supercomputing (ICS '17).
    [PDF] [Slides] [DOI] [BibTeX]

Invited Talks Supported by the Project

  • "OpenSPARSE: An Open Platform for Sparse Basic Linear Algebra Subprograms". Sparse Days Meeting (Sparse Days '18). Toulouse, France. September 27, 2018.

  • "Parallel Segmented Merge and Its Applications to Two Sparse Matrix Kernels". 8th SIAM Workshop on Combinatorial Scientific Computing (CSC '18). Bergen, Norway. June 8, 2018.
    [Abstract] [PDF] [Slides]

  • "Scalability Analysis of Sparse Triangular Solve". 13th SIAM Conference on Applied Linear Algebra (LA '18). Hong Kong, China. May 6, 2018.
    [Abstract] [Slides]

  • "When Sparse Matrices Met Heterogeneous Processors: Opportunities and Challenges". 18th SIAM Conference on Parallel Processing for Scientific Computing (PP '18). Tokyo, Japan. March 10, 2018.
    [Abstract] [Slides]

  • "Scalability Analysis of Sparse Matrix Computations on Many-core Processors". Sparse Days Meeting (Sparse Days '17). Toulouse, France. September 7, 2017.
    [Abstract] [Slides] [Video]