I am now a Postdoc at CUHK, and graduated from CUHK on Shenzhen campus for my PhD. My CV is da.

My research explores sparse workloads on modern computing hardware. I have a keen interest in tackling graph-related problems across a range of computing platforms, including CPUs with OpenMP, GPUs utilizing CUDA, and clusters utilizing MPI and RMDA.

At the heart of my research lies in the interplay between sparse matrices and dense computing. By delving into their conflicts, I aim to uncover strategies and techniques that can effectively harness the power of powerful computing units such as SIMD and Tensor Cores.

Specifically, I am looking into three types of research problems:

  • Parallel Graph algorithms, e,g, PageRank, BFS, Triangle Counting, etc.
  • Sparse matrix multiplication (SpMV, SpMM, SDDMM, SpGEMM) on CPUs and GPUs
  • Graph Neural Network & Sparse Deep Neural Network.

Also, I am a fan of modern C++ programming, particularly in the context of C++23.

In 2018, I received my dual master degrees in Multicore Systems from TU Eindhoven, Netherlands and TU Berlin, Germany with full scholarship granted by European Union. In 2017-2018, I worked as Masterarbeitor (i.e., intern) in Frauhofer FOKUS to build Germany’s e-health infrastructure, based on which I developed my master thesis “Providing the Infrastructure for SICCT Protocol Tests with Focus on Service Discovery and Pairing”.

In 2015, I obtained my bachelor degree at Huazhong University of Science and Technology (HUST). Also, in 2014-2015, being sponsored by CSC scholarship, I studied as an exchange student in RWTH Aachen, Germany.

Publications

YuAng Chen and Yeh-Ching Chung, “Workload Balancing via Graph Reordering on Multicore Systems,” IEEE Transactions on Parallel and Distributed Systems (TPDS), Vol. 33, No. 5, 2022, pp. 1231-1245.

YuAng Chen and Yeh-Ching Chung, “HiPa: Hierarchical Partitioning for Fast Page Rank on Multicore Systems,” Proceedings of IEEE International conference on Parallel Processing (ICPP), Article No. 24, 2021, pp. 1-10.

YuAng Chen and Yeh-Ching Chung, “Corder: Cache-Aware Reordering For Optimizing Graph Analytics,” Proceedings of ACM International conference on Principles and Practice of Parallel Programming (PPoPP), 2021, pp.472-473.

YuAng Chen and Yeh-Ching Chung, “A Unequal Caching Strategy for Shared-Memory Graph Analytics”, IEEE Transaction on Parallel and Distributed Systems (TPDS), Vol. 34, No. 3, 2023, pp. 955-967.

YuAng Chen and Yeh-Ching Chung, “Connectivity-Aware Link Analysis for Skewed Graphs,” Proceedings of International Conference on Parallel Processing (ICPP), pp. 482-491. 2023.

YuAng Chen and Jeffery Xu Yu. “Accelerating SpMV for Scale-Free Graphs with Optimized Bins.” In 2024 IEEE 40th International Conference on Data Engineering (ICDE), pp. 2407-2420. IEEE, 2024.

YuAng Chen and Jeffery Xu Yu, “Vectorized Sparse Blocks of Graph Matrices”, Euro-Par'24

YuAng Chen and Jeffery Xu Yu, “Bitmap-Based Sparse Matrix-Vector Multiplication with Tensor Cores”, ICPP'24

Ongoing Work

YuAng Chen and Yeh-Ching Chung, “Locality Extraction & Blocking for Graph Adjacency Matrix Multiplications”, under review

YuAng Chen and Jeffery Xu Yu, “Triangle Counting on Tensor Cores”, under review

Teaching

2020  Spring : Introduction to Programming Methodology
2020  Fall      : Operating System
2021  Spring : Compiler Design
2021  Fall      : Operating System
2022  Spring : Computer Architecture