{"title":"高阶和基于元组的大规模并行前缀和","authors":"Sepideh Maleki, Annie Yang, Martin Burtscher","doi":"10.1145/2908080.2908089","DOIUrl":null,"url":null,"abstract":"Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"93 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Higher-order and tuple-based massively-parallel prefix sums\",\"authors\":\"Sepideh Maleki, Annie Yang, Martin Burtscher\",\"doi\":\"10.1145/2908080.2908089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.\",\"PeriodicalId\":178839,\"journal\":{\"name\":\"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation\",\"volume\":\"93 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2908080.2908089\",\"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 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2908080.2908089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Higher-order and tuple-based massively-parallel prefix sums
Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.