@inproceedings{6e28da3366134eb0844c1959e68ce862,
title = "Understanding the Effects of Modern Compressors on the Community Earth Science Model",
abstract = "The Community Earth Science Model (CESM) is an important tool in climate modeling that produces a large volume of data on each simulation. Researchers have increasingly been turning to both lossless and lossy compression as an approach to reduce the volume of data for the CESM climate applications. Choosing the best-qualified compressor is nontrivial, however, especially because of the advent of many modern lossless and lossy compressors and complicated scientific integrity assessment of climate data model. In this paper we evaluate 11 state-of-the-art compressors using the quality assessments developed by climate scientists to understand the effectiveness of the compressors on the CESM climate datasets with four different models. Our work also identifies the best compression ratio that can be reasonably achieved while meeting these strict quality requirements.",
keywords = "CESM, lossless compression, lossy compression, MGARD, sz, ZFP",
author = "Robert Underwood and Julie Bessac and Sheng Di and Franck Cappello",
note = "Funding Information: This research was supported by the 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, Advanced Scientific Computing Research (ASCR), under contract DE-AC02-06CH11357, and supported by the National Science Foundation under Grant OAC-2003709 and OAC-2104023. We acknowledge the computing resources provided on Bebop (operated by Laboratory Computing Resource Center at Argonne). Publisher Copyright: {\textcopyright} 2022 IEEE.; 8th IEEE/ACM International Workshop on Data Analysis and Reduction for Big Scientific Data, DRBSD-8 2022 ; Conference date: 13-11-2022 Through 18-11-2022",
year = "2022",
doi = "10.1109/DRBSD56682.2022.00006",
language = "English (US)",
series = "Proceedings of DRBSD-8 2022: 8th International Workshop on Data Analysis and Reduction for Big Scientific Data, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--10",
booktitle = "Proceedings of DRBSD-8 2022",
address = "United States",
}