{"title":"并行稀疏多元多项式除法","authors":"M. Gastineau, J. Laskar","doi":"10.1145/2790282.2790285","DOIUrl":null,"url":null,"abstract":"We present a scalable algorithm for dividing two sparse multivariate polynomials represented in a distributed format on shared memory multicore computers. The scalability on the large number of cores is ensured by the lack of synchronizations during the main parallel step. The merge and sorting operations are based on binary heap or tree data structures.","PeriodicalId":384227,"journal":{"name":"Proceedings of the 2015 International Workshop on Parallel Symbolic Computation","volume":"50 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Parallel sparse multivariate polynomial division\",\"authors\":\"M. Gastineau, J. Laskar\",\"doi\":\"10.1145/2790282.2790285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a scalable algorithm for dividing two sparse multivariate polynomials represented in a distributed format on shared memory multicore computers. The scalability on the large number of cores is ensured by the lack of synchronizations during the main parallel step. The merge and sorting operations are based on binary heap or tree data structures.\",\"PeriodicalId\":384227,\"journal\":{\"name\":\"Proceedings of the 2015 International Workshop on Parallel Symbolic Computation\",\"volume\":\"50 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2015 International Workshop on Parallel Symbolic Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2790282.2790285\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 International Workshop on Parallel Symbolic Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2790282.2790285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a scalable algorithm for dividing two sparse multivariate polynomials represented in a distributed format on shared memory multicore computers. The scalability on the large number of cores is ensured by the lack of synchronizations during the main parallel step. The merge and sorting operations are based on binary heap or tree data structures.
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