A real-time garbage collector based on the lifetimes of objects
Communications of the ACM
Concurrent Remembered Set Refinement in Generational Garbage Collection
Proceedings of the 2nd Java Virtual Machine Research and Technology Symposium
Generation Scavenging: A non-disruptive high performance storage reclamation algorithm
SDE 1 Proceedings of the first ACM SIGSOFT/SIGPLAN software engineering symposium on Practical software development environments
Myths and realities: the performance impact of garbage collection
Proceedings of the joint international conference on Measurement and modeling of computer systems
Garbage-first garbage collection
Proceedings of the 4th international symposium on Memory management
Automatic heap sizing: taking real memory into account
Proceedings of the 4th international symposium on Memory management
Controlling garbage collection and heap growth to reduce the execution time of Java applications
ACM Transactions on Programming Languages and Systems (TOPLAS)
The DaCapo benchmarks: java benchmarking development and analysis
Proceedings of the 21st annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Intelligent selection of application-specific garbage collectors
Proceedings of the 6th international symposium on Memory management
Modeling, analysis and throughput optimization of a generational garbage collector
Proceedings of the 2009 international symposium on Memory management
Investigating the effects of using different nursery sizing policies on performance
Proceedings of the 2009 international symposium on Memory management
ParamILS: an automatic algorithm configuration framework
Journal of Artificial Intelligence Research
The economics of garbage collection
Proceedings of the 2010 international symposium on Memory management
Oracle JRockit: The Definitive Guide
Oracle JRockit: The Definitive Guide
Garbage collection auto-tuning for Java mapreduce on multi-cores
Proceedings of the international symposium on Memory management
Optimisation of virtual machine garbage collection policies
ASMTA'11 Proceedings of the 18th international conference on Analytical and stochastic modeling techniques and applications
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Garbage collection, if not tuned properly, can considerably impact application performance. Unfortunately, configuring a garbage collector is a tedious task as only few guidelines exist and tuning is often done by trial and error. We present what is, to our knowledge, the first published work on automatically tuning Java garbage collectors in a black-box manner considering all available parameters. We propose the use of iterated local search methods to automatically compute application-specific garbage collector configurations. Our experiments show that automatic tuning can reduce garbage collection time by up to 77% for a specific application and a specific workload and by 35% on average across all benchmarks (compared to the default configuration). We evaluated our approach for 3 different garbage collectors on the DaCapo and SPECjbb benchmarks, as well as on a real-world industrial application.