{"title":"管理性能分析与动态统计投影追求","authors":"J. Vetter, D. Reed","doi":"10.1145/331532.331576","DOIUrl":null,"url":null,"abstract":"Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focussing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.","PeriodicalId":354898,"journal":{"name":"ACM/IEEE SC 1999 Conference (SC'99)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Managing Performance Analysis with Dynamic Statistical Projection Pursuit\",\"authors\":\"J. Vetter, D. Reed\",\"doi\":\"10.1145/331532.331576\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focussing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.\",\"PeriodicalId\":354898,\"journal\":{\"name\":\"ACM/IEEE SC 1999 Conference (SC'99)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM/IEEE SC 1999 Conference (SC'99)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/331532.331576\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM/IEEE SC 1999 Conference (SC'99)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/331532.331576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Managing Performance Analysis with Dynamic Statistical Projection Pursuit
Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focussing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.