{"title":"通过基于分析的L1数据缓存绕过来提高GPU性能","authors":"Y. Huangfu, Wei Zhang","doi":"10.1109/CCGrid.2015.67","DOIUrl":null,"url":null,"abstract":"Cache memories have been introduced in recent generations of Graphics Processing Units (GPUs) to benefit general-purpose computing on GPUs (GPGPUs). In this work, we analyze the memory access patterns of GPGPU applications and propose a cost-effective profiling-based method to identify the data accesses that should bypass the L1 data cache to improve performance. The evaluation indicates that the proposed L1 cache bypassing can improve the GPU performance by 13.8% on average.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"9 1","pages":"1119-1122"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Boosting GPU Performance by Profiling-Based L1 Data Cache Bypassing\",\"authors\":\"Y. Huangfu, Wei Zhang\",\"doi\":\"10.1109/CCGrid.2015.67\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cache memories have been introduced in recent generations of Graphics Processing Units (GPUs) to benefit general-purpose computing on GPUs (GPGPUs). In this work, we analyze the memory access patterns of GPGPU applications and propose a cost-effective profiling-based method to identify the data accesses that should bypass the L1 data cache to improve performance. The evaluation indicates that the proposed L1 cache bypassing can improve the GPU performance by 13.8% on average.\",\"PeriodicalId\":6664,\"journal\":{\"name\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"volume\":\"9 1\",\"pages\":\"1119-1122\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCGrid.2015.67\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Boosting GPU Performance by Profiling-Based L1 Data Cache Bypassing
Cache memories have been introduced in recent generations of Graphics Processing Units (GPUs) to benefit general-purpose computing on GPUs (GPGPUs). In this work, we analyze the memory access patterns of GPGPU applications and propose a cost-effective profiling-based method to identify the data accesses that should bypass the L1 data cache to improve performance. The evaluation indicates that the proposed L1 cache bypassing can improve the GPU performance by 13.8% on average.
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