{"title":"RVVRadar:一个支持RISC-V矢量化编程的框架","authors":"Lucas Klemmer, Manfred Schlägl, Daniel Große","doi":"10.1145/3526241.3530388","DOIUrl":null,"url":null,"abstract":"In this paper, we present RVVRadar, a framework to support the programmer over the four major steps of development, verification, measurement, and evaluation during the vectorization process of an algorithm. We demonstrate the advantages of RVVRadar for vectorization on several practical relevant algorithms. This includes in particular the widely-used libpng library where we vectorized all filter computations resulting in speedups of up to 5.43. We made RVVRadar as well as all benchmarks (including the RVV-based libpng) open source.","PeriodicalId":188228,"journal":{"name":"Proceedings of the Great Lakes Symposium on VLSI 2022","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"RVVRadar: A Framework for Supporting the Programmer in Vectorization for RISC-V\",\"authors\":\"Lucas Klemmer, Manfred Schlägl, Daniel Große\",\"doi\":\"10.1145/3526241.3530388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present RVVRadar, a framework to support the programmer over the four major steps of development, verification, measurement, and evaluation during the vectorization process of an algorithm. We demonstrate the advantages of RVVRadar for vectorization on several practical relevant algorithms. This includes in particular the widely-used libpng library where we vectorized all filter computations resulting in speedups of up to 5.43. We made RVVRadar as well as all benchmarks (including the RVV-based libpng) open source.\",\"PeriodicalId\":188228,\"journal\":{\"name\":\"Proceedings of the Great Lakes Symposium on VLSI 2022\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Great Lakes Symposium on VLSI 2022\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3526241.3530388\",\"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 Great Lakes Symposium on VLSI 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3526241.3530388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
RVVRadar: A Framework for Supporting the Programmer in Vectorization for RISC-V
In this paper, we present RVVRadar, a framework to support the programmer over the four major steps of development, verification, measurement, and evaluation during the vectorization process of an algorithm. We demonstrate the advantages of RVVRadar for vectorization on several practical relevant algorithms. This includes in particular the widely-used libpng library where we vectorized all filter computations resulting in speedups of up to 5.43. We made RVVRadar as well as all benchmarks (including the RVV-based libpng) open source.
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