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
2013-05-01
Proceedings Title
Proceedings of the ACM International Conference on Computing Frontiers - CF '13
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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