{"title":"Compression Speed Enhancements to LZO for Multi-core Systems","authors":"Jason Kane, Qing Yang","doi":"10.1109/SBAC-PAD.2012.29","DOIUrl":null,"url":null,"abstract":"This paper examines several promising throughput enhancements to the Lempel-Ziv-Oberhumer (LZO) 1x-1-15 data compression algorithm. Of many algorithm variants present in the current library version, 2.06, LZO 1x-1-15 is considered to be the fastest, geared toward speed rather than compression ratio. We present several algorithm modifications tailored to modern multi-core architectures in this paper that are intended to increase compression speed while minimizing any loss in compression ratio. On average, the experimental results show that on a modern quad core system, a 3.9x speedup in compression time is achieved over the baseline algorithm with no loss to compression ratio. Allowing for a 25% loss in compression ratio, up to a 5.4x speedup in compression time was observed.","PeriodicalId":232444,"journal":{"name":"2012 IEEE 24th International Symposium on Computer Architecture and High Performance Computing","volume":"216 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 24th International Symposium on Computer Architecture and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBAC-PAD.2012.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper examines several promising throughput enhancements to the Lempel-Ziv-Oberhumer (LZO) 1x-1-15 data compression algorithm. Of many algorithm variants present in the current library version, 2.06, LZO 1x-1-15 is considered to be the fastest, geared toward speed rather than compression ratio. We present several algorithm modifications tailored to modern multi-core architectures in this paper that are intended to increase compression speed while minimizing any loss in compression ratio. On average, the experimental results show that on a modern quad core system, a 3.9x speedup in compression time is achieved over the baseline algorithm with no loss to compression ratio. Allowing for a 25% loss in compression ratio, up to a 5.4x speedup in compression time was observed.
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