SIMD扩展导出分支的矢量化方法

2011 10th IEEE/ACIS International Conference on Computer and Information Science Pub Date : 2011-05-16 DOI:10.1109/ICIS.2011.49

Jiafeng Zhu, Rongcai Zhao, Lin Han, Yunlong Hao, Lili Bai

{"title":"SIMD扩展导出分支的矢量化方法","authors":"Jiafeng Zhu, Rongcai Zhao, Lin Han, Yunlong Hao, Lili Bai","doi":"10.1109/ICIS.2011.49","DOIUrl":null,"url":null,"abstract":"The main popular vectorization methods for the SIMD extension dig the parallelism of the programs relying on the compiler's data dependence analysis. But the data dependence analysis can not deal with the non-structured control flow statements. Therefore, the up-to-date compilers are extremely limited to vectorize these statements. Here is a vectorization method of the export branch for the SIMD extension, which can automatically and effectively vectorize the export branch within the vector length. And the results of performance test show that this method can both fully ensure the semantic correctness of the control flow and exploit the parallelism of the data flow.","PeriodicalId":256762,"journal":{"name":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Vectorization Method of Export Branch for SIMD Extension\",\"authors\":\"Jiafeng Zhu, Rongcai Zhao, Lin Han, Yunlong Hao, Lili Bai\",\"doi\":\"10.1109/ICIS.2011.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main popular vectorization methods for the SIMD extension dig the parallelism of the programs relying on the compiler's data dependence analysis. But the data dependence analysis can not deal with the non-structured control flow statements. Therefore, the up-to-date compilers are extremely limited to vectorize these statements. Here is a vectorization method of the export branch for the SIMD extension, which can automatically and effectively vectorize the export branch within the vector length. And the results of performance test show that this method can both fully ensure the semantic correctness of the control flow and exploit the parallelism of the data flow.\",\"PeriodicalId\":256762,\"journal\":{\"name\":\"2011 10th IEEE/ACIS International Conference on Computer and Information Science\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 10th IEEE/ACIS International Conference on Computer and Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIS.2011.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIS.2011.49","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

目前流行的SIMD扩展向量化方法主要依靠编译器的数据依赖性分析来挖掘程序的并行性。但是数据相关性分析不能处理非结构化的控制流语句。因此，最新的编译器在向量化这些语句方面受到极大限制。本文提出了一种SIMD扩展导出分支的矢量化方法，该方法可以在矢量长度范围内自动有效地对导出分支进行矢量化。性能测试结果表明，该方法既能充分保证控制流的语义正确性，又能充分利用数据流的并行性。

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

A Vectorization Method of Export Branch for SIMD Extension

The main popular vectorization methods for the SIMD extension dig the parallelism of the programs relying on the compiler's data dependence analysis. But the data dependence analysis can not deal with the non-structured control flow statements. Therefore, the up-to-date compilers are extremely limited to vectorize these statements. Here is a vectorization method of the export branch for the SIMD extension, which can automatically and effectively vectorize the export branch within the vector length. And the results of performance test show that this method can both fully ensure the semantic correctness of the control flow and exploit the parallelism of the data flow.

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

2011 10th IEEE/ACIS International Conference on Computer and Information Science

自引率

0.00%

发文量