@inproceedings{81bbd96e1ad54b878c9200189c726aa9,
title = "Fixed-PSNR Lossy Compression for Scientific Data",
abstract = "Error-controlled lossy compression has been studied for years because of extremely large volumes of data being produced by today's scientific simulations. None of existing lossy compressors, however, allow users to fix the peak signal-to-noise ratio (PSNR) during compression, although PSNR has been considered as one of the most significant indicators to assess compression quality. In this paper, we propose a novel technique providing a fixed-PSNR lossy compression for scientific data sets. We implement our proposed method based on the SZ lossy compression framework and release the code as an open-source toolkit. We evaluate our fixed-PSNR compressor on three realworld high-performance computing data sets. Experiments show that our solution has a high accuracy in controlling PSNR, with an average deviation of 0.1 ~ 5.0 dB on the tested data sets.",
keywords = "Lossy compression, PSNR, Scientific data",
author = "Dingwen Tao and Sheng Di and Xin Liang and Zizhong Chen and Franck Cappello",
note = "Funding Information: ACKNOWLEDGE This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations – the Office of Science and the National Nuclear Security Administration, responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, to support the nation{\textquoteright}s exascale computing imperative. The material was supported by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357,and supported by the National Science Foundation under Grant No. 1619253. We gratefully acknowledge the computing resources provided on Bebop, a high-performance computing cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 ; Conference date: 10-09-2018 Through 13-09-2018",
year = "2018",
month = oct,
day = "29",
doi = "10.1109/CLUSTER.2018.00048",
language = "English (US)",
series = "Proceedings - IEEE International Conference on Cluster Computing, ICCC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "314--318",
booktitle = "Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018",
address = "United States",
}