Controlling garbage collection and heap growth to reduce the execution time of Java applications
OOPSLA '01 Proceedings of the 16th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Understanding the connectivity of heap objects
Proceedings of the 3rd international symposium on Memory management
In or out?: putting write barriers in their place
Proceedings of the 3rd international symposium on Memory management
On the usefulness of type and liveness accuracy for garbage collection and leak detection
ACM Transactions on Programming Languages and Systems (TOPLAS)
Concurrent Remembered Set Refinement in Generational Garbage Collection
Proceedings of the 2nd Java Virtual Machine Research and Technology Symposium
Oil and Water? High Performance Garbage Collection in Java with MMTk
Proceedings of the 26th International Conference on Software Engineering
Myths and realities: the performance impact of garbage collection
Proceedings of the joint international conference on Measurement and modeling of computer systems
Dynamic selection of application-specific garbage collectors
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)
On the Prediction of Java Object Lifetimes
IEEE Transactions on Computers
The DaCapo benchmarks: java benchmarking development and analysis
Proceedings of the 21st annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Deconstructing process isolation
Proceedings of the 2006 workshop on Memory system performance and correctness
Singularity: rethinking the software stack
ACM SIGOPS Operating Systems Review - Systems work at Microsoft Research
Application-specific garbage collection
Journal of Systems and Software
Sealing OS processes to improve dependability and safety
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Intelligent selection of application-specific garbage collectors
Proceedings of the 6th international symposium on Memory management
Influence of program inputs on the selection of garbage collectors
Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
The study and handling of program inputs in the selection of garbage collectors
ACM SIGOPS Operating Systems Review
A comparative evaluation of parallel garbage collector implementations
LCPC'01 Proceedings of the 14th international conference on Languages and compilers for parallel computing
ECOOP'07 Proceedings of the 2007 conference on Object-oriented technology
Implementation, compilation, optimization of object-oriented languages, programs and systems
ECOOP'06 Proceedings of the 2006 conference on Object-oriented technology: ECOOP 2006 workshop reader
Z-rays: divide arrays and conquer speed and flexibility
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Garbage collection auto-tuning for Java mapreduce on multi-cores
Proceedings of the international symposium on Memory management
Hi-index | 0.00 |
Many garbage-collected systems use a single garbage collection algorithm across all applications. It has long been known that this can produce poor performance on applications for which that collector is not well suited. In some systems, such as those that execute stand-alone compiled executables, an appropriate collector for each application can be selected from a pool of available collectors and tuned by using profile information. In a study of 20 benchmarks and several collectors, compiled with the Marmot optimizing Java-to-native compiler, for every collector there was at least one benchmark that would have been at least 15% faster with a more appropriate collector. The collectors are a copying collector, a generational copying collector, which is combined with each of 4 different write barriers, and the null collector, which allocates but never collects. A detailed analysis of storage management costs shows how they vary by application and collector.