{"title":"Java8的并行在线精确求和","authors":"Naoshi Sakamoto","doi":"10.1109/ICIS.2016.7550817","DOIUrl":null,"url":null,"abstract":"Java8 introduced the notion of streams that is a new data structure and supports multi-core processors. When the sum method is called for a stream of floating-point numbers, the summation is calculated at high-speed by applying MapReduce, which distributes computations to cores. However, since floating-point calculation causes an error, simple adaptation of this method can not determine the result uniquely. Then, in this study, we develop a summation program that can be applied to a stream with MapReduce. Our method can calculate at high-speed with keeping correctly rounded.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Parallel online exact sum for Java8\",\"authors\":\"Naoshi Sakamoto\",\"doi\":\"10.1109/ICIS.2016.7550817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Java8 introduced the notion of streams that is a new data structure and supports multi-core processors. When the sum method is called for a stream of floating-point numbers, the summation is calculated at high-speed by applying MapReduce, which distributes computations to cores. However, since floating-point calculation causes an error, simple adaptation of this method can not determine the result uniquely. Then, in this study, we develop a summation program that can be applied to a stream with MapReduce. Our method can calculate at high-speed with keeping correctly rounded.\",\"PeriodicalId\":336322,\"journal\":{\"name\":\"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIS.2016.7550817\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIS.2016.7550817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Java8 introduced the notion of streams that is a new data structure and supports multi-core processors. When the sum method is called for a stream of floating-point numbers, the summation is calculated at high-speed by applying MapReduce, which distributes computations to cores. However, since floating-point calculation causes an error, simple adaptation of this method can not determine the result uniquely. Then, in this study, we develop a summation program that can be applied to a stream with MapReduce. Our method can calculate at high-speed with keeping correctly rounded.
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