Selected Publications (*(first author)[Conference/Journal Name][Research Topics] "Paper Name")
PhD Thesis
Exploiting Data Sparsity in Matrix Algorithms for Adaptive Optics and Seismic Redatuming [Link]
2024
*[IJHPCA][TLR-MVM, GPU, Mixed Precision] "HPC Seismic Redatuming by Inversion with Algebraic Compression and Multiple Precisions", Yuxi Hong, Hatem Ltaief, Matteo Ravasi, David Keyes. The International Journal of High Performance Computing Applications, Sage Publications.
2023
[SC' 23, ACM Gordon Bell Price Finalist][TLR-MVM, Cerebras] "Scaling the “Memory Wall” for Multi-Dimensional Seismic Processing with Algebraic Compression on Cerebras CS-2 Systems", Hatem Ltaief, Yuxi Hong, Leighton Wilson, Mathias Jacquelin, Matteo Ravasi, David Keyes. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Nov 12 - 17, 2023, Denvor CO, USA. [Link][ACM Gordon Bell Finalists Introduction]
[ISC' 23][TLR-MVM, Graphcore] "Steering Customized AI Architectures for HPC Scientific Applications" Hatem Ltaief, Yuxi Hong, Adel Dabah, Rabab Alomairy, Sameh Abdulah, Chris Goreczny, Pawel Gepner, Matteo Ravasi, Damien Gratadour & David Keyes. International Conference on High Performance Computing, pp. (125-143), Springer Publications. [Link]
[IMAGE' 23][Seismic Redatuming, TLR-MVM] "Can tile low-rank compression live up to expectations? An application to 3D multidimensional deconvolution" Yuxi Hong, Matteo Ravasi, Hatem Ltaief, and David Keyes. Third International Meeting for Applied Geoscience & Energy Expanded Abstracts, 2023. [Link]
2022
[IMAGE' 22][Seismic Redatuming, TLR-MVM] "Large-scale Marchenko imaging with distance-aware matrix reordering, tile low-rank compression, and mixed-precision computations" Matteo Ravasi, Yuxi Hong, Hatem Ltaief, David Keyes, and David Vargas. Second International Meeting for Applied Geoscience & Energy 2022. [Link]
[EAGE' 22][Seismic Redatuming, TLR-MVM] "Tile-Low Rank Compressed Multi-Dimensional Convolution and Its Application to Seismic Redatuming Problems" Matteo Ravasi, Yuxi Hong, Hatem Ltaief, David Keyes. 83rd EAGE Annual Conference & Exhibition, Jun 2022, Volume 2022, p.1 - 5. [Link]
2021
*[SFI][TLR-MVM, NEC Vector Engine] "Accelerating seismic redatuming using tile low-rank approximations on NEC SX-aurora TSUBASA" Yuxi Hong, Hatem Ltaief, Matteo Ravasi, Laurent Gatineau, David Keyes. SUPERCOMPUTING FRONTIERS AND INNOVATIONS, Vol. 8 No. 2 (2021): Special Issue on Advance Methods and Technologies on Vector Computing and Data-Processing Using NEC SX-Aurora TSUBASA Architecture. [Link]
[SC' 21][TLR-MVM, MPI, OpenMP] "Meeting the real-time challenges of ground-based telescopes using low-rank matrix computations" Hatem Ltaief, Jesse Cranney, Damien Gratadour, Yuxi Hong, Laurent Gatineau, David Keyes. The International Conference for High Performance Computing, Networking, Storage and Analysis, November 14 - 19, 2021, St. Louis, Missouri, USA. [Link]
*[EuroPar' 21][Stochastic Optimization, Computational Astronomy] "Outsmarting the Atmospheric Turbulence for Ground-Based Telescopes Using the Stochastic Levenberg-Marquardt Method" Yuxi Hong, El Houcine Bergou, Nicolas Doucet, Hao Zhang, Jesse Cranney, Hatem Ltaief, Damien Gratadour, Francois Rigaut, David Keyes. European Conference on Parallel Processing 2021. [Link]
*[Big Data Research][Efficient Deep Learning, Sparsification] "LSDDL: Layer-Wise Sparsification for Distributed Deep Learning" Yuxi Hong, Peng Han. Big Data Research, Volume 26, 15 November 2021. [Link]
Before 2021
*[ISCV' 18][Computer Vision] "End-to-end soccer video scene and event classification with deep transfer learning" Yuxi Hong, Chen Ling, Zuochang Ye. 2018 International Conference on Intelligent Systems and Computer Vision. [Link]
*[JOS][Statistical Learning] "Multivariate rational regression and its application in semiconductor device modeling" Yuxi Hong, Dongsheng Ma, Zuochang Ye. Journal of Semiconductors, Volume 39, Number 9, 2018. [Link]
[Journal of Selected Topics in Quantum Electronics][Sensor] "Simultaneous Distributed Acoustic and Temperature Sensing Using a Multimode Fiber" Yuan Mao, Islam Ashry, Frode Hveding, Ahmed Y. Bukhamsin, Yuxi Hong, Tien Khee Ng. Boon S. Ooi. IEEE Journal of Selected Topics in Quantum Electronics, Volume 26, Issue 4, July-August 2020. [Link]
Services (Program Committee)
2024 : ICPP Parallel Computing
Journal Review: Parallel Computing
Softwares
https://github.com/ecrc/tlrmvm (main developer)
https://github.com/DIG-Kaust/TLR-MDC (main developer)
https://github.com/PASSIONLab/CombBLAS (contributor)
https://github.com/ecrc/kblas-gpu (contributor)
Short Biography
Yuxi Hong is a postdoctoral research fellow in the Performance and Algorithms group of the Computer Science Department at Lawrence Berkeley National Laboratory. He obtained his Ph.D. in Computer Science at King Abdullah University of Science and Technology (KAUST). He received an MS degree in Electronics Engineering from Tsinghua University and a BSc from Tsinghua University. His current research interests include HPC, Numerical Linear Algebra, GPU programming, sparse computation, low rank methods and efficient Machine Learning/ Deep learning. My PhD advisors are David Keyes, Hatem Ltaief and Matteo Ravasi.