{"title":"用于Java完全垃圾收集的可伸缩和高效的压缩","authors":"Haoyu Li, Mingyu Wu, B. Zang, Haibo Chen","doi":"10.1145/3313808.3313820","DOIUrl":null,"url":null,"abstract":"Java runtime frees applications from manual memory management through automatic garbage collection (GC). This, however, is usually at the cost of stop-the-world pauses. State-of-the-art collectors leverage multiple generations, which will inevitably suffer from a full GC phase scanning and compacting the whole heap. This induces a pause tens of times longer than normal collections, which largely affects both throughput and latency of applications. In this paper, we comprehensively analyze the full GC performance of the Parallel Scavenge garbage collector in HotSpot. We find that chain-like dependencies among heap regions cause low thread utilization and poor scalability. Furthermore, many heap regions are filled with live objects (referred to as dense regions), which are unnecessary to collect. To address these two problems, we provide , which contains two main optimizations: dynamically allocating shadow regions as compaction destinations to eliminate region dependencies and skipping dense regions to reduce GC workload. Evaluation results against the HotSpot JVM of OpenJDK 8/11 show that works on most benchmarks and leads to 5.6X/5.1X improvement at best in full GC throughput and thereby boost the application performance by up to 61.8%/49.0%.","PeriodicalId":350040,"journal":{"name":"Proceedings of the 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"ScissorGC: scalable and efficient compaction for Java full garbage collection\",\"authors\":\"Haoyu Li, Mingyu Wu, B. Zang, Haibo Chen\",\"doi\":\"10.1145/3313808.3313820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Java runtime frees applications from manual memory management through automatic garbage collection (GC). This, however, is usually at the cost of stop-the-world pauses. State-of-the-art collectors leverage multiple generations, which will inevitably suffer from a full GC phase scanning and compacting the whole heap. This induces a pause tens of times longer than normal collections, which largely affects both throughput and latency of applications. In this paper, we comprehensively analyze the full GC performance of the Parallel Scavenge garbage collector in HotSpot. We find that chain-like dependencies among heap regions cause low thread utilization and poor scalability. Furthermore, many heap regions are filled with live objects (referred to as dense regions), which are unnecessary to collect. To address these two problems, we provide , which contains two main optimizations: dynamically allocating shadow regions as compaction destinations to eliminate region dependencies and skipping dense regions to reduce GC workload. Evaluation results against the HotSpot JVM of OpenJDK 8/11 show that works on most benchmarks and leads to 5.6X/5.1X improvement at best in full GC throughput and thereby boost the application performance by up to 61.8%/49.0%.\",\"PeriodicalId\":350040,\"journal\":{\"name\":\"Proceedings of the 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3313808.3313820\",\"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 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3313808.3313820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ScissorGC: scalable and efficient compaction for Java full garbage collection
Java runtime frees applications from manual memory management through automatic garbage collection (GC). This, however, is usually at the cost of stop-the-world pauses. State-of-the-art collectors leverage multiple generations, which will inevitably suffer from a full GC phase scanning and compacting the whole heap. This induces a pause tens of times longer than normal collections, which largely affects both throughput and latency of applications. In this paper, we comprehensively analyze the full GC performance of the Parallel Scavenge garbage collector in HotSpot. We find that chain-like dependencies among heap regions cause low thread utilization and poor scalability. Furthermore, many heap regions are filled with live objects (referred to as dense regions), which are unnecessary to collect. To address these two problems, we provide , which contains two main optimizations: dynamically allocating shadow regions as compaction destinations to eliminate region dependencies and skipping dense regions to reduce GC workload. Evaluation results against the HotSpot JVM of OpenJDK 8/11 show that works on most benchmarks and leads to 5.6X/5.1X improvement at best in full GC throughput and thereby boost the application performance by up to 61.8%/49.0%.