{"title":"自动调优Java虚拟机","authors":"Sanath Jayasena, Milinda Fernando, Tharindu Rusira Patabandi, Chalitha Perera, C. Philips","doi":"10.1109/IPDPSW.2015.84","DOIUrl":null,"url":null,"abstract":"We address the problem of tuning the performance of the Java Virtual Machine (JVM) with run-time flags (parameters). We use the Hot Spot JVM in our study. As the Hot Spot JVM comes with over 600 flags to choose from, selecting a subset manually to maximize performance is infeasible. In prior work, the potential performance improvement is limited by the fact that only a subset of the tunable flags are tuned. We adopt a different approach and present the Hot Spot Auto-tuner which considers the entire JVM and the effect of all the flags. To the best of our knowledge, ours is the first auto-tuner for optimizing the performance of the JVM as a whole. We organize the JVM flags into a tree structure by building a flag-hierarchy, which helps us to resolve dependencies on aspects of the JVM such as garbage collector algorithms and JIT compilation, and helps to reduce the configuration search-space. Experiments with the SPECjvm2008 and DaCapo benchmarks show that we could optimize the Hot Spot JVM with significant speedup, 16 SPECjvm2008 startup programs were improved by an average of 19% with three of them improved dramatically by 63%, 51% and 32% within a maximum tuning time of 200 minutes for each. Based on a minimum tuning time of 200 minutes, average performance improvement for 13 DaCapo benchmark programs is 26% with 42% being the maximum improvement.","PeriodicalId":340697,"journal":{"name":"2015 IEEE International Parallel and Distributed Processing Symposium Workshop","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Auto-Tuning the Java Virtual Machine\",\"authors\":\"Sanath Jayasena, Milinda Fernando, Tharindu Rusira Patabandi, Chalitha Perera, C. Philips\",\"doi\":\"10.1109/IPDPSW.2015.84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We address the problem of tuning the performance of the Java Virtual Machine (JVM) with run-time flags (parameters). We use the Hot Spot JVM in our study. As the Hot Spot JVM comes with over 600 flags to choose from, selecting a subset manually to maximize performance is infeasible. In prior work, the potential performance improvement is limited by the fact that only a subset of the tunable flags are tuned. We adopt a different approach and present the Hot Spot Auto-tuner which considers the entire JVM and the effect of all the flags. To the best of our knowledge, ours is the first auto-tuner for optimizing the performance of the JVM as a whole. We organize the JVM flags into a tree structure by building a flag-hierarchy, which helps us to resolve dependencies on aspects of the JVM such as garbage collector algorithms and JIT compilation, and helps to reduce the configuration search-space. Experiments with the SPECjvm2008 and DaCapo benchmarks show that we could optimize the Hot Spot JVM with significant speedup, 16 SPECjvm2008 startup programs were improved by an average of 19% with three of them improved dramatically by 63%, 51% and 32% within a maximum tuning time of 200 minutes for each. Based on a minimum tuning time of 200 minutes, average performance improvement for 13 DaCapo benchmark programs is 26% with 42% being the maximum improvement.\",\"PeriodicalId\":340697,\"journal\":{\"name\":\"2015 IEEE International Parallel and Distributed Processing Symposium Workshop\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Parallel and Distributed Processing Symposium Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPDPSW.2015.84\",\"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 IEEE International Parallel and Distributed Processing Symposium Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW.2015.84","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We address the problem of tuning the performance of the Java Virtual Machine (JVM) with run-time flags (parameters). We use the Hot Spot JVM in our study. As the Hot Spot JVM comes with over 600 flags to choose from, selecting a subset manually to maximize performance is infeasible. In prior work, the potential performance improvement is limited by the fact that only a subset of the tunable flags are tuned. We adopt a different approach and present the Hot Spot Auto-tuner which considers the entire JVM and the effect of all the flags. To the best of our knowledge, ours is the first auto-tuner for optimizing the performance of the JVM as a whole. We organize the JVM flags into a tree structure by building a flag-hierarchy, which helps us to resolve dependencies on aspects of the JVM such as garbage collector algorithms and JIT compilation, and helps to reduce the configuration search-space. Experiments with the SPECjvm2008 and DaCapo benchmarks show that we could optimize the Hot Spot JVM with significant speedup, 16 SPECjvm2008 startup programs were improved by an average of 19% with three of them improved dramatically by 63%, 51% and 32% within a maximum tuning time of 200 minutes for each. Based on a minimum tuning time of 200 minutes, average performance improvement for 13 DaCapo benchmark programs is 26% with 42% being the maximum improvement.