{"title":"有效地计算堆栈距离","authors":"G. Almási, Calin Cascaval, D. Padua","doi":"10.1145/773146.773043","DOIUrl":null,"url":null,"abstract":"This paper1 describes our experience using the stack processing algorithm [6] for estimating the number of cache misses in scientific programs. By using a new data structure and various optimization techniques we obtain instrumented run-times within 50 to 100 times the original optimized run-times of our benchmarks.","PeriodicalId":365109,"journal":{"name":"Memory System Performance","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"132","resultStr":"{\"title\":\"Calculating stack distances efficiently\",\"authors\":\"G. Almási, Calin Cascaval, D. Padua\",\"doi\":\"10.1145/773146.773043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper1 describes our experience using the stack processing algorithm [6] for estimating the number of cache misses in scientific programs. By using a new data structure and various optimization techniques we obtain instrumented run-times within 50 to 100 times the original optimized run-times of our benchmarks.\",\"PeriodicalId\":365109,\"journal\":{\"name\":\"Memory System Performance\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"132\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Memory System Performance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/773146.773043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Memory System Performance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/773146.773043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper1 describes our experience using the stack processing algorithm [6] for estimating the number of cache misses in scientific programs. By using a new data structure and various optimization techniques we obtain instrumented run-times within 50 to 100 times the original optimized run-times of our benchmarks.
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