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  • 1.
    Klaftenegger, David
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Brief announcement: queue delegation locking2014In: Proc. 26th ACM Symposium on Parallelism in Algorithms and Architectures, New York: ACM Press, 2014, p. 70-72Conference paper (Refereed)
  • 2.
    Klaftenegger, David
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Delegation locking libraries for improved performance of multithreaded programs2014In: Euro-Par 2014: Parallel Processing, Springer Berlin/Heidelberg, 2014, Vol. 8632, p. 572-583Conference paper (Refereed)
  • 3.
    Klaftenegger, David
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    On the scalability of the Erlang term storage2013In: Proc. 12th ACM SIGPLAN Workshop on Erlang, New York: ACM Press, 2013, p. 15-26Conference paper (Refereed)
  • 4.
    Klaftenegger, David
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Queue Delegation Locking2018In: IEEE Transactions on Parallel and Distributed Systems, ISSN 1045-9219, E-ISSN 1558-2183, Vol. 29, no 3, p. 687-704Article in journal (Refereed)
    Abstract [en]

    The scalability of parallel programs is often bounded by the performance of synchronization mechanisms used to protect critical sections. The performance of these mechanisms is in turn determined by their sequential execution time, efficient use of hardware, and ability to avoid waiting. In this article, we describe queue delegation (QD) locking, a family of locks that both delegate critical sections and enable detaching execution. Threads delegate work to the thread currently holding the lock and are able to detach, i.e., immediately continue their execution until they need a result from a previously delegated critical section. We show how to use queue delegation to build synchronization algorithms with lower overhead and higher throughput than existing algorithms, even when critical sections need to communicate results back immediately. Experiments when using up to 64 threads to access a shared priority queue show that QD locking provides 10 times higher throughput than Pthreads mutex locks and outperforms leading delegation algorithms. Also, when mixing parallel reads with delegated write operations, QD locking outperforms competing algorithms with an advantage ranging from 9.5 up to 207 percent increased throughput. Last but not least, continuing execution instead of waiting for the execution of critical sections leads to increased parallelism and better scalability. As we will see, queue delegation locking uses simple building blocks whose overhead is low even in uncontended use. All these make the technique useful in a wide variety of applications.

  • 5.
    Sagonas, Konstantinos
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Natl Tech Univ Athens, Sch Elect & Comp Engn, Athens, Greece..
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    A contention adapting approach to concurrent ordered sets2018In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 115, p. 1-19Article in journal (Refereed)
    Abstract [en]

    With multicores being ubiquitous, concurrent data structures are increasingly important. This article proposes a novel approach to concurrent data structure design where the data structure dynamically adapts its synchronization granularity based on the detected contention and the amount of data that operations are accessing. This approach not only has the potential to reduce overheads associated with synchronization in uncontended scenarios, but can also be beneficial when the amount of data that operations are accessing atomically is unknown. Using this adaptive approach we create a contention adapting search tree (CA tree) that can be used to implement concurrent ordered sets and maps with support for range queries and bulk operations. We provide detailed proof sketches for the linearizability as well as deadlock and livelock freedom of CA tree operations. We experimentally compare CA trees to state-of-the-art concurrent data structures and show that CA trees beat the best of the data structures that we compare against by over 50% in scenarios that contain basic set operations and range queries, outperform them by more than 1200% in scenarios that also contain range updates, and offer performance and scalability that is better than many of them on workloads that only contain basic set operations.

  • 6.
    Sagonas, Konstantinos
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Natl Tech Univ Athens, Sch ECE, GR-10682 Athens, Greece.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Contention adapting search trees2015In: Proc. 14th International Symposium on Parallel and Distributed Computing, IEEE conference proceedings, 2015, p. 215-224Conference paper (Refereed)
    Abstract [en]

    With multicores being ubiquitous, concurrent data structures are becoming increasingly important. This paper proposes a novel approach to concurrent data structure design where the data structure collects statistics about contention and adapts dynamically according to this statistics. We use this approach to create a contention adapting binary search tree (CA tree) that can be used to implement concurrent ordered sets and maps. Our experimental evaluation shows that CA trees scale similar to recently proposed algorithms on a big multicore machine on various scenarios with a larger set size, and outperform the same data structures in more contended scenarios and in sequential performance. We also show that CA trees are well suited for optimization with hardware lock elision. In short, we propose a practically useful and easy to implement and show correct concurrent search tree that naturally adapts to the level of contention.

  • 7.
    Sagonas, Konstantinos
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    More scalable ordered set for ETS using adaptation2014In: Proc. 13th ACM SIGPLAN Workshop on Erlang, New York: ACM Press, 2014, p. 3-11Conference paper (Refereed)
  • 8.
    Sagonas, Konstantinos
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    The Contention Avoiding Concurrent Priority Queue2017In: Languages and Compilers for Parallel Computing, Springer, 2017, p. 314-330Conference paper (Refereed)
  • 9.
    Trinder, Phil
    et al.
    University of Glasgow, Glasgow, Scotland.
    Chechina, Natalia
    University of Glasgow, Glasgow, Scotland.
    Papaspyrou, Nikolaos
    Natl Tech Univ Athens, Athens, Greece.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Natl Tech Univ Athens, Athens, Greece.
    Thompson, Simon
    University of Kent.
    Adams, Stephen
    University of Kent.
    Aronis, Stavros
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Baker, Robert
    University of Kent.
    Bihari, Eva
    Erlang Solutions.
    Boudeville, Olivier
    Électricité de France.
    Cesarini, Francesco
    Erlang Solutions.
    Di Stefano, Maurizio
    University of Kent.
    Eriksson, Sverker
    Ericsson AB.
    Fördős, Viktória
    Erlang Solutions.
    Ghaffari, Amir
    University of Glasgow, Glasgow, Scotland.
    Giantsios, Aggelos
    Natl Tech Univ Athens, Athens, Greece.
    Green, Rickard
    Ericsson AB.
    Hoch, Csaba
    Erlang Solutions.
    Klaftenegger, David
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Li, Huiqing
    University of Kent.
    Lundin, Kenneth
    Ericsson AB.
    Mackenzie, Kenneth
    University of Glasgow, Glasgow, Scotland.
    Roukounaki, Katerina
    Natl Tech Univ Athens, Athens, Greece.
    Tsiouris, Yiannis
    Natl Tech Univ Athens, Athens, Greece.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Scaling Reliably: Improving the scalability of the Erlang distributed actor platform2017In: ACM Transactions on Programming Languages and Systems, ISSN 0164-0925, E-ISSN 1558-4593, Vol. 39, no 4, article id 17Article in journal (Refereed)
  • 10.
    Winblad, Kjell
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.
    Dynamic Adaptations of Synchronization Granularity in Concurrent Data Structures2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The multicore revolution means that programmers have many cores at their disposal in everything from phones to large server systems. Concurrent data structures are needed to make good use of all the cores. Designing a concurrent data structure that performs well across many different scenarios is a difficult task. The reason for this is that the best synchronization granularity and data organization vary between scenarios. Furthermore, the number of parallel threads and the types of operations that are accessing a data structure may even change over time.

    This dissertation tackles the problem mentioned above by proposing concurrent data structures that dynamically adapt their synchronization granularity and organization based on usage statistics collected at run-time. Two of these data structures (one lock-free and one lock-based) implement concurrent sets with support for range queries and other multi-item operations. These data structures adapt their synchronization granularity based on detected contention and the number of items that are involved in multi-item operations such as range queries. This dissertation also proposes a concurrent priority queue that dynamically changes its precision based on detected contention.

    Experimental evaluations of the proposed data structures indicate that they outperform non-adaptive data structures over a wide range of scenarios because they adapt their synchronization based on usage statistics. Possible practical consequences of the work described in this dissertation are faster parallel programs and a reduced need to manually tune the synchronization granularities of concurrent data structures.

    List of papers
    1. A contention adapting approach to concurrent ordered sets
    Open this publication in new window or tab >>A contention adapting approach to concurrent ordered sets
    2018 (English)In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 115, p. 1-19Article in journal (Refereed) Published
    Abstract [en]

    With multicores being ubiquitous, concurrent data structures are increasingly important. This article proposes a novel approach to concurrent data structure design where the data structure dynamically adapts its synchronization granularity based on the detected contention and the amount of data that operations are accessing. This approach not only has the potential to reduce overheads associated with synchronization in uncontended scenarios, but can also be beneficial when the amount of data that operations are accessing atomically is unknown. Using this adaptive approach we create a contention adapting search tree (CA tree) that can be used to implement concurrent ordered sets and maps with support for range queries and bulk operations. We provide detailed proof sketches for the linearizability as well as deadlock and livelock freedom of CA tree operations. We experimentally compare CA trees to state-of-the-art concurrent data structures and show that CA trees beat the best of the data structures that we compare against by over 50% in scenarios that contain basic set operations and range queries, outperform them by more than 1200% in scenarios that also contain range updates, and offer performance and scalability that is better than many of them on workloads that only contain basic set operations.

    Place, publisher, year, edition, pages
    ACADEMIC PRESS INC ELSEVIER SCIENCE, 2018
    Keywords
    Concurrent data structures, Ordered sets, Linearizability, Range queries
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-351559 (URN)10.1016/j.jpdc.2017.11.007 (DOI)000427809200001 ()
    Available from: 2018-05-30 Created: 2018-05-30 Last updated: 2018-06-18Bibliographically approved
    2. More scalable ordered set for ETS using adaptation
    Open this publication in new window or tab >>More scalable ordered set for ETS using adaptation
    2014 (English)In: Proc. 13th ACM SIGPLAN Workshop on Erlang, New York: ACM Press, 2014, p. 3-11Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    New York: ACM Press, 2014
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-234579 (URN)10.1145/2633448.2633455 (DOI)978-1-4503-3038-1 (ISBN)
    Conference
    Erlang 2014
    Projects
    RELEASEUPMARC
    Available from: 2014-09-03 Created: 2014-10-21 Last updated: 2018-06-18Bibliographically approved
    3. Lock-free Contention Adapting Search Trees
    Open this publication in new window or tab >>Lock-free Contention Adapting Search Trees
    2018 (English)In: The 30th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2018, New York, NY, USA, 2018, Vol. 30Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    New York, NY, USA: , 2018
    National Category
    Computer and Information Sciences
    Research subject
    Computer Science
    Identifiers
    urn:nbn:se:uu:diva-354022 (URN)10.1145/3210377.3210413 (DOI)978-1-4503-5799-9 (ISBN)
    Conference
    The 30th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2018, July 16–18, 2018, Vienna, Austria
    Funder
    Swedish Research Council
    Note

    In press

    Available from: 2018-06-18 Created: 2018-06-18 Last updated: 2018-06-27Bibliographically approved
    4. Delegation locking libraries for improved performance of multithreaded programs
    Open this publication in new window or tab >>Delegation locking libraries for improved performance of multithreaded programs
    2014 (English)In: Euro-Par 2014: Parallel Processing, Springer Berlin/Heidelberg, 2014, Vol. 8632, p. 572-583Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Springer Berlin/Heidelberg, 2014
    Series
    Lecture Notes in Computer Science ; 8632
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-234577 (URN)10.1007/978-3-319-09873-9_48 (DOI)978-3-319-09872-2 (ISBN)
    Conference
    20th International European Conference on Parallel Processing, Porto, Portugal, August 25-29, 2014
    Projects
    UPMARCRELEASE
    Available from: 2014-08-29 Created: 2014-10-21 Last updated: 2018-06-18Bibliographically approved
    5. The Contention Avoiding Concurrent Priority Queue
    Open this publication in new window or tab >>The Contention Avoiding Concurrent Priority Queue
    2017 (English)In: Languages and Compilers for Parallel Computing, Springer, 2017, p. 314-330Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Springer, 2017
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 ; 10136
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-346764 (URN)10.1007/978-3-319-52709-3_23 (DOI)000413069500023 ()978-3-319-52708-6 (ISBN)
    Conference
    LCPC 2016, September 27–30, Rochester, NY
    Available from: 2017-01-24 Created: 2018-03-26 Last updated: 2018-06-18Bibliographically approved
  • 11.
    Winblad, Kjell
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jonsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Lock-free Contention Adapting Search Trees2018In: The 30th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2018, New York, NY, USA, 2018, Vol. 30Conference paper (Refereed)
1 - 11 of 11
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