{"title":"用于声音浮点计算的间隔编译器","authors":"Joao Rivera, F. Franchetti, Markus Püschel","doi":"10.1109/CGO51591.2021.9370307","DOIUrl":null,"url":null,"abstract":"Floating-point arithmetic is widely used by software developers but is unsound, i.e., there is no guarantee on the accuracy obtained, which can be imperative in safety-critical applications. We present IGen, a source-to-source compiler that translates a given C function using floating-point into an equivalent sound C function that uses interval arithmetic. IGen supports Intel SIMD intrinsics in the input function using a specially designed code generator and can produce SIMD-optimized output. To mitigate a possible loss of accuracy due to the increase of interval sizes, IGen can compile to double-double precision, again SIMD-optimized. Finally, IGen implements an accuracy optimization for the common reduction pattern. We benchmark our compiler on high-performance code in the domain of linear algebra and signal processing. The results show that the generated code delivers sound double precision results at high performance. In particular, we observe speed-ups of up to 9.8 when compared to commonly used interval libraries using double precision. When compiling to double-double, our compiler delivers intervals that keep error accumulation small enough to compute results with at most one bit of error in double precision, i.e., certified double precision results.","PeriodicalId":275062,"journal":{"name":"2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An Interval Compiler for Sound Floating-Point Computations\",\"authors\":\"Joao Rivera, F. Franchetti, Markus Püschel\",\"doi\":\"10.1109/CGO51591.2021.9370307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Floating-point arithmetic is widely used by software developers but is unsound, i.e., there is no guarantee on the accuracy obtained, which can be imperative in safety-critical applications. We present IGen, a source-to-source compiler that translates a given C function using floating-point into an equivalent sound C function that uses interval arithmetic. IGen supports Intel SIMD intrinsics in the input function using a specially designed code generator and can produce SIMD-optimized output. To mitigate a possible loss of accuracy due to the increase of interval sizes, IGen can compile to double-double precision, again SIMD-optimized. Finally, IGen implements an accuracy optimization for the common reduction pattern. We benchmark our compiler on high-performance code in the domain of linear algebra and signal processing. The results show that the generated code delivers sound double precision results at high performance. In particular, we observe speed-ups of up to 9.8 when compared to commonly used interval libraries using double precision. When compiling to double-double, our compiler delivers intervals that keep error accumulation small enough to compute results with at most one bit of error in double precision, i.e., certified double precision results.\",\"PeriodicalId\":275062,\"journal\":{\"name\":\"2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CGO51591.2021.9370307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGO51591.2021.9370307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Interval Compiler for Sound Floating-Point Computations
Floating-point arithmetic is widely used by software developers but is unsound, i.e., there is no guarantee on the accuracy obtained, which can be imperative in safety-critical applications. We present IGen, a source-to-source compiler that translates a given C function using floating-point into an equivalent sound C function that uses interval arithmetic. IGen supports Intel SIMD intrinsics in the input function using a specially designed code generator and can produce SIMD-optimized output. To mitigate a possible loss of accuracy due to the increase of interval sizes, IGen can compile to double-double precision, again SIMD-optimized. Finally, IGen implements an accuracy optimization for the common reduction pattern. We benchmark our compiler on high-performance code in the domain of linear algebra and signal processing. The results show that the generated code delivers sound double precision results at high performance. In particular, we observe speed-ups of up to 9.8 when compared to commonly used interval libraries using double precision. When compiling to double-double, our compiler delivers intervals that keep error accumulation small enough to compute results with at most one bit of error in double precision, i.e., certified double precision results.