Huizhang Luo, a recipient of the Yuelu Scholar Morning Star A position and selected for the Hunan Province Talents Program, obtained his Bachelor’s degree in Computer Science and Technology in 2012 and his Ph.D. in 2017, both from Chongqing University. He conducted postdoctoral research at New Jersey Institute of Technology, USA, from July 2017 to December 2020. Currently, he serves as an associate professor in the Department of Computer Science at the College of Information Science and Engineering, Hunan University. His primary research interests include high-performance computing and computer architecture.
Publications
This part collects a(n incomplete) list of Huizhang Luo’s publications. Posters and workshp papers without formal proceedings are not recorded. More information is available at Google Scholar and dblp.
[TECS 2024]
AMP: Total Variation Reduction for Lossless Compression via Approximate Median-based Preconditioning
Fenfang Li, Huizhang Luo, Junqi Wang, Yida Li, Zhuo Tang, Kenli Li
ACM Transactions on Embedded Computing Systems, 2024
[TVT 2024]
MF-Net: A Multimodal Fusion Model for Fast Multi-object Tracking
Shirui Tian, Mingxing Duan, Jiayan Deng, Huizhang Luo, Yikun Hu
IEEE Transactions on Vehicular Technology, 2024
[TPDS 2023]
COFFEE: Cross-Layer Optimization for Fast and Efficient Executions of Sinkhorn-Knopp Algorithm on HPC Systems
Chengyu Sun, Huizhang Luo, Hong Jiang, Jeff Zhang, Kenli Li
IEEE Transactions on Parallel and Distributed Systems, 2023
[TC 2023]
LAMP: Improving compression ratio for AMR applications via level associated mapping-based preconditioning
Yida Li, Huizhang Luo, Fenfang Li, Junqi Wang, Kenli Li
IEEE Transactions on Computers, vol. 72, no. 12, pp. 3370–3382, 2023.
[TPDS 2022]
zMesh: Theories and Methods to Exploring Application Characteristics to Improve Lossy Compression Ratio for Adaptive Mesh Refinement
Huizhang Luo, Junqi Wang, Qing Liu, Jieyang Chen, Scott Klasky, Norbert Podhorszki
IEEE Transactions on Parallel and Distributed Systems, 2022
[IPDPS 2021]
zmesh: Exploring application characteristics to improve lossy compression ratio for adaptive mesh refinement
Huizhang Luo, Junqi Wang, Qing Liu, Jieyang Chen, Scott Klasky, Norbert Podhorszki
2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
[IPDPS 2019]
Identifying latent reduced models to precondition lossy compression
Huizhang Luo, Dan Huang, Qing Liu, Zhenbo Qiao, Hong Jiang, Jing Bi, Haitao Yuan, Mengchu Zhou, Jinzhen Wang, Zhenlu Qin
2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
[IPDPS 2018]
Understanding and modeling lossy compression schemes on HPC scientific data
Tao Lu, Qing Liu, Xubin He, Huizhang Luo, Eric Suchyta, Jong Choi, Norbert Podhorszki, Scott Klasky, Mathew Wolf, Tong Liu, Zhenbo Qiao
2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)