{"title":"Lossy Scientific Data Compression With SPERR","authors":"Shaomeng Li, P. Lindstrom, J. Clyne","doi":"10.1109/IPDPS54959.2023.00104","DOIUrl":null,"url":null,"abstract":"As the need for data reduction in high-performance computing (HPC) continues to grow, we introduce a new and highly effective tool to help achieve this goal—SPERR. SPERR is a versatile lossy compressor for structured scientific data; it is built on top of an advanced wavelet compression algorithm, SPECK, and provides additional capabilities valued in HPC environments. These capabilities include parallel execution for large volumes and a compression mode that satisfies a maximum point-wise error tolerance. Evaluation shows that in most settings SPERR achieves the best rate-distortion trade-off among current popular lossy scientific data compressors.","PeriodicalId":343684,"journal":{"name":"2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS54959.2023.00104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
As the need for data reduction in high-performance computing (HPC) continues to grow, we introduce a new and highly effective tool to help achieve this goal—SPERR. SPERR is a versatile lossy compressor for structured scientific data; it is built on top of an advanced wavelet compression algorithm, SPECK, and provides additional capabilities valued in HPC environments. These capabilities include parallel execution for large volumes and a compression mode that satisfies a maximum point-wise error tolerance. Evaluation shows that in most settings SPERR achieves the best rate-distortion trade-off among current popular lossy scientific data compressors.
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