Concurrent size
The size of a data structure (i.e., the number of elements in it) is a widely used property of a data set. However, for concurrent programs, obtaining a correct size efficiently is non-trivial. In fact, the literature does not offer a mechanism to obtain a correct (linearizable) size of a concurrent...
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| Published in: | Proceedings of ACM on programming languages Vol. 6; no. OOPSLA2; pp. 345 - 372 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY, USA
ACM
31.10.2022
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| Subjects: | |
| ISSN: | 2475-1421, 2475-1421 |
| Online Access: | Get full text |
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| Summary: | The size of a data structure (i.e., the number of elements in it) is a widely used property of a data set. However, for concurrent programs, obtaining a correct size efficiently is non-trivial. In fact, the literature does not offer a mechanism to obtain a correct (linearizable) size of a concurrent data set without resorting to inefficient solutions, such as taking a full snapshot of the data structure to count the elements, or acquiring one global lock in all update and size operations. This paper presents a methodology for adding a concurrent linearizable size operation to sets and dictionaries with a relatively low performance overhead. Theoretically, the proposed size operation is wait-free with asymptotic complexity linear in the number of threads (independently of data-structure size). Practically, we evaluated the performance overhead by adding size to various concurrent data structures in Java−a skip list, a hash table and a tree. The proposed linearizable size operation executes faster by orders of magnitude compared to the existing option of taking a snapshot, while incurring a throughput loss of 1%−20% on the original data structure’s operations. |
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| ISSN: | 2475-1421 2475-1421 |
| DOI: | 10.1145/3563300 |