Below are recent publications, full list publications can be found at LINK1 and LINK2.
GCSM: GPU-Accelerated Continuous Subgraph Matching for Large Graphs
Yihua Wei, Peng Jiang
[IPDPS’24]: IEEE International Parallel and Distributed Processing Symposium, 2024
cuKE: An Efficient Code Generator for Score Function Computation in Knowledge Graph Embedding
Lihan Hu, Jing Li, and Peng Jiang
[IPDPS’24]: IEEE International Parallel and Distributed Processing Symposium, 2024
DRUTO: Upper-Bounding Silent Data Corruption Vulnerability in GPU Applications
Md Hasanur Rahman, Sheng Di, Shengjian Guo, Xiaoyi Lu, Guanpeng Li, and Franck Cappello
[IPDPS’24]: IEEE International Parallel and Distributed Processing Symposium, 2024
Characterizing Runtime Performance Variation in Error Detection by Duplicating Instructions
Yafan Huang*, Zhengyang He*, Lingda Li, and Guanpeng Li
[ISSRE’23]: IEEE International Symposium on Software Reliability Engineering (* co-first authors)
cuSZp: An Ultra-Fast GPU Error-Bounded Lossy Compression Framework with Optimized End-to-End Performance
Yafan Huang, Sheng Di, Xiaodong Yu, Guanpeng Li, and Franck Cappello
[SC’23] International Conference for High-Performance Computing, Networking, Storage and Analysis, 2023
Demystifying and Mitigating Cross-Layer Deficiencies of Soft Error Protection in Instruction Duplication
Zhengyang He, Yafan Huang, Hui Xu, Dingwen Tao, and Guanpeng Li
[SC’23] International Conference for High-Performance Computing, Networking, Storage and Analysis, 2023
Towards Improving Reverse Time Migration Performance by High-speed Lossy Compression
Yafan Huang, Kai Zhao, Sheng Di, Guanpeng Li, Maxim Dmitriev, Thierry-Laurent D. Tonellot, Franck Cappello
[CCGrid’23] THE 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing
A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets
Md Hasanur Rahman, Sheng Di, Kai Zhao, Robert Underwood, Guanpeng Li, Franck Cappello
[ICDE’23] The 39th IEEE International Conference on Data Engineering
SALUS: A Novel Data-Driven Approach for Enabling Real-Time Safety of Autonomous Vehicles
Bohan Zhang, Yafan Huang, Guanpeng Li
[QRS’22] IEEE International Conference on Software Quality, Reliability, and Security
Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training
Peng Jiang, Lihan Hu, Shihui Song
[NeurIPS’22] Thirty-sixth Conference on Neural Information Processing Systems
SampleMine: A Framework for Applying Random Sampling to Subgraph Pattern Mining through Loop Perforation
Peng Jiang, Yihua Wei, Jiya Su, Rujia Wang, Bo Wu
[PACT’22] The 31st International Conference on Parallel Architectures and Compilation Techniques
STMatch: Accelerating Graph Pattern Matching On GPU with Stack-Based Loop Optimization
Yihua Wei, Peng Jiang
[SC’22] International Conference for High-Performance Computing, Networking, Storage and Analysis, 2022
Mitigating Silent Data Corruptions in HPC Applications across Multiple Program Inputs
Yafan Huang, Shengjian Guo, Sheng Di, Guanpeng Li, Franck Cappello
[SC’22] International Conference for High-Performance Computing, Networking, Storage and Analysis, 2022
Best Paper Finalist, Best Student Paper Finalist
Rethinking Graph Data Placement for Graph Neural Network Training on Multiple GPUs
Shihui Song, Peng Jiang
[ICS’22] ACM International Conference on Supercomputing, 2022
Peppa-X: Finding Program Test Inputs to Bound Silent Data Corruption Vulnerability in HPC Applications
Md Hasanur Rahman, Aabid Shamji, Shengjian Guo, Guanpeng Li
[SC’21] International Conference for High-Performance Computing, Networking, Storage and Analysis, 2021
Exploring PIM Architecture for High-Performance Graph Pattern Mining
Jiya Su, Linfeng He, Peng Jiang, Rujia Wang
[CAL’21] IEEE Computer Architecture Letters
Accelerating Sparse CNN Inference on GPUs with Performance-Aware Weight Pruning
Masuma Akter Rumi, Xiaolong Ma, Yanzhi Wang, Peng Jiang
[PACT’20] The 29th International Conference on Parallel Architectures and Compilation Techniques, 2020