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An efficient parallel heap compaction algorithm
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Source Conference on Object Oriented Programming Systems Languages and Applications archive
Proceedings of the 19th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications table of contents
Vancouver, BC, Canada
SESSION: Java technologies table of contents
Pages: 224 - 236  
Year of Publication: 2004
ISBN:1-58113-831-9
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Authors
Diab Abuaiadh  IBM Haifa Research Laboratory, Mount Carmel, Haifa, ISRAEL
Yoav Ossia  IBM Haifa Research Laboratory, Mount Carmel, Haifa, ISRAEL
Erez Petrank  Dept. of Computer Science, Technion - Israel Institute of Technology, Haifa, Israel
Uri Silbershtein  IBM Haifa Research Laboratory, Mount Carmel, Haifa, ISRAEL
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 52,   Citation Count: 8
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Diab Abuaiadh: colleagues
Yoav Ossia: colleagues
Erez Petrank: colleagues
Uri Silbershtein: colleagues