Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Author:

Chen Jieyang,Wan Lipeng,Liang Xin,Whitney Ben,Liu Qing,Pugmire David,Thompson Nicholas,Choi Jong Youl,Wolf Matthew,Munson Todd,Foster Ian,Klasky Scott

Funder

Office of Science

Publisher

IEEE

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Concealing Compression-accelerated I/O for HPC Applications through In Situ Task Scheduling;Proceedings of the Nineteenth European Conference on Computer Systems;2024-04-22

2. Fast Algorithms for Scientific Data Compression;2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC);2023-12-18

3. cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance;Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis;2023-11-11

4. Online and Scalable Data Compression Pipeline with Guarantees on Quantities of Interest;2023 IEEE 19th International Conference on e-Science (e-Science);2023-10-09

5. FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs;Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing;2023-08-07

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