Abstract

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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