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Space-and-time efficient garbage collectors for parallel systems
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Conference On Computing Frontiers archive
Proceedings of the 6th ACM conference on Computing frontiers table of contents
Ischia, Italy
SESSION: Innovative memory systems table of contents
Pages 21-30  
Year of Publication: 2009
ISBN:978-1-60558-413-3
Authors
Shaoshan Liu  University of California, Irvine, Irvine, CA, USA
Ligang Wang  Intel China Research Center, Beijing, China
Xiao-Feng Li  Intel China Research Center, Beijing, China
Jean-Luc Gaudiot  University of California, Irvine, Irvine, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
Publisher
ACM  New York, NY, USA
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ABSTRACT

As multithreaded server applications and runtime systems prevail, garbage collection is becoming an essential feature to support high performance systems. The fundamental issue of garbage collector (GC) design is to maximize the recycled space with minimal time overhead. This paper proposes two innovative solutions: one to improve space efficiency, and the other to improve time efficiency. To achieve space efficiency, we propose the Space Tuner that utilizes the novel concept of allocation speed to reduce wasted space. Conventional static space partitioning techniques often lead to inefficient space utilization. The Space Tuner adjusts the heap partitioning dynamically such that when a collection is triggered, all space partitions are fully filled. To achieve time efficiency, we propose a novel parallelization method that reduces the compacting GC parallelization problem into a tree traversal parallelization problem. This method can be applied for both normal and large object compaction. Object compaction is hard to parallelize due to strong data dependencies such that the source object can not be moved to its target location until the object originally in the target location has been moved out. Our proposed algorithm overcomes the difficulties by dividing the heap into equal-sized blocks and parallelizing the movement of the independent blocks. It is noteworthy that these proposed algorithms are generic such that they can be utilized in different GC designs.


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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Apache Harmony: Open-Source Java SE. http://harmony.apache.org/
 
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Dacapo Project: The DaCapo Benchmark Suite. http://www-ali.cs.umass.edu/dacapo/index.html
 
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Ming Wu and Xiao-Feng Li, Task-pushing: a Scalable Parallel GC Marking Algorithm without Synchronization Operations. In Proceedings of IEEE International Parallel and Distributed Processing Symposium, Long Beach, California, 2007.
 
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Common Language Runtime Overview. http://msdn.microsoft.com/en-us/library/ddk909ch(vs.71).aspx
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Collaborative Colleagues:
Shaoshan Liu: colleagues
Ligang Wang: colleagues
Xiao-Feng Li: colleagues
Jean-Luc Gaudiot: colleagues