平衡稠密多元乘法:一般情况

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI:10.1109/SYNASC57785.2022.00015

M. M. Maza, Haoze Yuan

{"title":"平衡稠密多元乘法:一般情况","authors":"M. M. Maza, Haoze Yuan","doi":"10.1109/SYNASC57785.2022.00015","DOIUrl":null,"url":null,"abstract":"We propose general preprocessing techniques to reshape dense multivariate polynomials over finite fields, in order to minimize the cost of memory accesses, while preserving sufficient parallelism, so as to reduce the running time of polynomial multiplication in multi-threaded implementations.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Balanced Dense Multivariate Multiplication: The General Case\",\"authors\":\"M. M. Maza, Haoze Yuan\",\"doi\":\"10.1109/SYNASC57785.2022.00015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose general preprocessing techniques to reshape dense multivariate polynomials over finite fields, in order to minimize the cost of memory accesses, while preserving sufficient parallelism, so as to reduce the running time of polynomial multiplication in multi-threaded implementations.\",\"PeriodicalId\":446065,\"journal\":{\"name\":\"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC57785.2022.00015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC57785.2022.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

我们提出了一种通用的预处理技术来重构有限域上的密集多元多项式，以最小化内存访问成本，同时保持足够的并行性，从而减少多线程实现中多项式乘法的运行时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Balanced Dense Multivariate Multiplication: The General Case

We propose general preprocessing techniques to reshape dense multivariate polynomials over finite fields, in order to minimize the cost of memory accesses, while preserving sufficient parallelism, so as to reduce the running time of polynomial multiplication in multi-threaded implementations.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

自引率

0.00%

发文量