Garbage collection: algorithms for automatic dynamic memory management
Garbage collection: algorithms for automatic dynamic memory management
Comparison of Compacting Algorithms for Garbage Collection
ACM Transactions on Programming Languages and Systems (TOPLAS)
A time- and space-efficient garbage compaction algorithm
Communications of the ACM
An efficient parallel heap compaction algorithm
OOPSLA '04 Proceedings of the 19th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Reducing generational copy reserve overhead with fallback compaction
Proceedings of the 5th international symposium on Memory management
The Compressor: concurrent, incremental, and parallel compaction
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Parallel garbage collection for shared memory multiprocessors
JVM'01 Proceedings of the 2001 Symposium on JavaTM Virtual Machine Research and Technology Symposium - Volume 1
The mapping collector: virtual memory support for generational, parallel, and concurrent compaction
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Memory management for many-core processors with software configurable locality policies
Proceedings of the 2012 international symposium on Memory Management
Adaptive scanning reduces sweep time for the Lisp2 mark-compact garbage collector
Proceedings of the 2013 international symposium on memory management
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Compacting garbage collector (GC) is widely used due to its good properties of in-place collection and heap de-fragmentation. In addition, it supports fast bump-pointer allocation and provides good access locality. Most known commercial JVM or CLR implementations use compaction algorithm in certain garbage collection scenarios, such as in full heap or mature object space collections. LISP2 compactor is one of the best-known GC algorithms. As multi-core architecture prevails, several efficient parallel compactors have been proposed. Nevertheless, there is no parallel LISP2 compactor available that can preserve all the sliding properties of its sequential counterpart. That is, to compact live data in-place into a single contiguous region in one end of the heap while maintaining the original object order. In this paper, we propose a fully parallel LISP2 compactor that keeps all the sliding properties. We also prove the correctness of the design. This parallel LISP2 compactor is fully parallel because all of its four phases are parallelized and the workloads are well balanced among the collector threads. The compactor supports fall-back compaction and adjustable boundaries that help deliver the best performance. We have implemented the parallel LISP2 compactor in Apache Harmony, a product-quality open source Java SE implementation. We evaluate and discuss the design on an Intel 8-core platform with representative benchmark.