Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation
Haas A, Lippautz M, Henzinger TA, Payer H, Sokolova A, Kirsch CM, Sezgin A. 2013. Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation. Proceedings of the ACM International Conference on Computing Frontiers - CF ’13. CF: Conference on Computing Frontiers, 17.
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Conference Paper
| Published
| English
Scopus indexed
Author
Haas, Andreas;
Lippautz, Michael;
Henzinger, Thomas AISTA 
;
Payer, Hannes;
Sokolova, Ana;
Kirsch, Christoph M.;
Sezgin, AliISTA
;
Payer, Hannes;
Sokolova, Ana;
Kirsch, Christoph M.;
Sezgin, AliISTADepartment
Abstract
A prominent remedy to multicore scalability issues in concurrent data structure implementations is to relax the sequential specification of the data structure. We present distributed queues (DQ), a new family of relaxed concurrent queue implementations. DQs implement relaxed queues with linearizable emptiness check and either configurable or bounded out-of-order behavior or pool behavior. Our experiments show that DQs outperform and outscale in micro- and macrobenchmarks all strict and relaxed queue as well as pool implementations that we considered.
Publishing Year
Date Published
2013-05-14
Proceedings Title
Proceedings of the ACM International Conference on Computing Frontiers - CF '13
Publisher
ACM Press
Acknowledgement
This work has been supported by the European Research Council advanced grant on Quantitative Reactive Modeling (QUAREM) and the National Research Network RiSE on Rigorous Systems Engineering (Austrian Science Fund S11402-N23 and S11404-N23).
Issue
5
Article Number
17
Conference
CF: Conference on Computing Frontiers
Conference Location
Ischia, Italy
Conference Date
2013-05-14 – 2013-05-16
ISBN
IST-REx-ID
Cite this
Haas A, Lippautz M, Henzinger TA, et al. Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation. In: Proceedings of the ACM International Conference on Computing Frontiers - CF ’13. ACM Press; 2013. doi:10.1145/2482767.2482789
Haas, A., Lippautz, M., Henzinger, T. A., Payer, H., Sokolova, A., Kirsch, C. M., & Sezgin, A. (2013). Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation. In Proceedings of the ACM International Conference on Computing Frontiers - CF ’13. Ischia, Italy: ACM Press. https://doi.org/10.1145/2482767.2482789
Haas, Andreas, Michael Lippautz, Thomas A Henzinger, Hannes Payer, Ana Sokolova, Christoph M. Kirsch, and Ali Sezgin. “Distributed Queues in Shared Memory: Multicore Performance and Scalability through Quantitative Relaxation.” In Proceedings of the ACM International Conference on Computing Frontiers - CF ’13. ACM Press, 2013. https://doi.org/10.1145/2482767.2482789.
A. Haas et al., “Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation,” in Proceedings of the ACM International Conference on Computing Frontiers - CF ’13, Ischia, Italy, 2013, no. 5.
Haas A, Lippautz M, Henzinger TA, Payer H, Sokolova A, Kirsch CM, Sezgin A. 2013. Distributed queues in shared memory: Multicore performance and scalability through quantitative relaxation. Proceedings of the ACM International Conference on Computing Frontiers - CF ’13. CF: Conference on Computing Frontiers, 17.
Haas, Andreas, et al. “Distributed Queues in Shared Memory: Multicore Performance and Scalability through Quantitative Relaxation.” Proceedings of the ACM International Conference on Computing Frontiers - CF ’13, no. 5, 17, ACM Press, 2013, doi:10.1145/2482767.2482789.
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