OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration

Author:

Underwood Robert1ORCID,Calhoun Jon C.2ORCID,Di Sheng1ORCID,Apon Amy2ORCID,Cappello Franck1

Affiliation:

1. Argonne National Laboratory Mathematics and Computer Science Division, Lemont, IL, USA

2. Clemson University, Clemson, SC, USA

Funder

National Science Foundation

Exascale Computing

U.S. Department of Energy

National Nuclear Security Administration

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

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

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2. SECRE: Surrogate-Based Error-Controlled Lossy Compression Ratio Estimation Framework;2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC);2023-12-18

3. LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12

4. A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

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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