An algorithm for parallel incremental compaction

Ben-Yitzhak, Ori; Goft, Irit; Kolodner, Elliot K.; Kuiper, Kean; Leikehman, Victor

doi:10.1145/512429.512442

Cited by 36 publications

References 9 publications

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MC ²

Sachindran

Moss

Berger

2004

Proceedings of the 19th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications

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Java is becoming an important platform for memory-constrained consumer devices such as PDAs and cellular phones, because it provides safety and portability. Since Java uses garbage collection, efficient garbage collectors that run in constrained memory are essential. Typical collection techniques used on these devices are mark-sweep and mark-compact. Mark-sweep collectors can provide good throughput and pause times but suffer from fragmentation. Mark-compact collectors prevent fragmentation, have low space overheads, and provide good throughput. However, they can suffer from long pause times.Copying collectors can provide higher throughput than either of these techniques, but because of their high space overhead, they previously were unsuitable for memory-constrained devices. This paper presents MC 2 (Memory-Constrained Copying), a copying generational garbage collector that meets the needs of memory-constrained devices with soft real-time requirements. MC 2 has low space overhead and tight space bounds, prevents fragmentation, provides good throughput, and yields short pause times. These qualities make MC 2 attractive for other environments, including desktops and servers.

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MC ²

Sachindran

Moss

Berger

2004

Proceedings of the 19th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications

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An efficient parallel heap compaction algorithm

Abuaiadh

Ossia

Petrank

et al. 2004

Proceedings of the 19th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications

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We propose a heap compaction algorithm appropriate for modern computing environments. Our algorithm is targeted at SMP platforms. It demonstrates high scalability when running in parallel but is also extremely efficient when running single-threaded on a uniprocessor. Instead of using the standard forwarding pointer mechanism for updating pointers to moved objects, the algorithm saves information for a pack of objects. It then does a small computation to process this information and determine each object's new location. In addition, using a smart parallel moving strategy, the algorithm achieves (almost) perfect compaction in the lower addresses of the heap, whereas previous algorithms achieved parallelism by compacting within several predetermined segments.Next, we investigate a method that trades compaction quality for a further reduction in time and space overhead. Finally, we propose a modern version of the two-finger compaction algorithm. This algorithm fails, thus, re-validating traditional wisdom asserting that retaining the order of live objects significantly improves the quality of the compaction.The parallel compaction algorithm was implemented on the IBM production Java Virtual Machine. We provide measurements demonstrating high efficiency and scalability. Subsequently, this algorithm has been incorporated into the IBM production JVM.

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Mostly concurrent compaction for mark-sweep GC

Ossia

Ben-Yitzhak

Segal

2004

Proceedings of the 4th International Symposium on Memory Management

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A memory manager that does not move objects may suffer from memory fragmentation. Compaction is an efficient, and sometimes inevitable, mechanism for reducing fragmentation. A Mark-Sweep garbage collector must occasionally execute a compaction, usually while the application is suspended. Compaction during pause time can have detrimental effects for interactive applications that require guarantees for maximal pause time. This work presents a method for reducing the pause time created by compaction at a negligible throughput hit. The solution is most suitable when added to a Mark-Sweep garbage collector.Compaction normally consists of two major activities: the moving of objects and the update of all the objects' references to the new locations. We present a method for executing the reference updates concurrently, thus eliminating a substantial portion of the pause time hit. To reduce the time for moving objects in each compaction, we use the existing technique of incremental compaction, but select the optimal area to compact. Selecting the area is done after executing the mark and sweep phases, and is based on their results.We implemented our compaction on top of the IBM J9 JVM V2.2, and present measurements of its effect on pause time, throughput, and mutator utilization. We show that our compaction is indeed an efficient fragmentation reduction tool, and that it improves the performance of a few of the benchmarks we used, with very little increase in the pause time (typically far below the cost of the mark phase).

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An algorithm for parallel incremental compaction

Cited by 36 publications

References 9 publications

MC ²

MC ²

An efficient parallel heap compaction algorithm

Mostly concurrent compaction for mark-sweep GC

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