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  • 251.
    Zafari, Afshin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Advances in Task-Based Parallel Programming for Distributed Memory Architectures2018Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    It has become common knowledge that parallel programming is needed for scientific applications, particularly for running large scale simulations. Different programming models are introduced for simplifying parallel programming, while enabling an application to use the full computational capacity of the hardware. In task-based programming, all the variables in the program are abstractly viewed as data. Parallelism is provided by partitioning the data. A task is a collection of operations performed on input data to generate output data. In distributed memory environments, the data is distributed over the computational nodes (or processes), and is communicated when a task needs remote data.

    This thesis discusses advanced techniques in distributed task-based parallel programming, implemented in the DuctTeip software library. DuctTeip uses MPI (Message Passing Interface) for asynchronous inter-process communication and Pthreads for shared memory parallelization within the processes. The data dependencies that determine which subsets of tasks can be executed in parallel are extracted from information about the data accesses (input or output) of the tasks. A versioning system is used internally to represent the task-data dependencies efficiently. A hierarchical partitioning of tasks and data allows for independent optimization of the size of computational tasks and the size of communicated data. A data listener technique is used to manage communication efficiently.

    DuctTeip provides an algorithm independent dynamic load balancing functionality. Redistributing tasks from busy processes to idle processes dynamically can provide an overall shorter execution time. A random search method with high probability of success is employed for locating idle/busy nodes.

    The advantage of the abstract view of tasks and data is exploited in a unified programming interface, which provides a standard for task-based frameworks to decouple framework development from application development. The interface can be used for collaboration between different frameworks in running an application program efficiently on different hardware.

    To evaluate the DuctTeip programming model, applications such as Cholesky factorization, a time-dependent PDE solver for the shallow water equations, and the fast multipole method have been implemented using DuctTeip. Experiments show that DuctTeip provides both scalability and performance. Comparisons with similar frameworks such as StarPU, OmpSs, and PaRSEC show competitive results.

    Delarbeid
    1. Programming models based on data versioning for dependency-aware task-based parallelisation
    Åpne denne publikasjonen i ny fane eller vindu >>Programming models based on data versioning for dependency-aware task-based parallelisation
    2012 (engelsk)Inngår i: Proc. 15th International Conference on Computational Science and Engineering, Los Alamitos, CA: IEEE Computer Society, 2012, s. 275-280Konferansepaper, Publicerat paper (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Los Alamitos, CA: IEEE Computer Society, 2012
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-187446 (URN)10.1109/ICCSE.2012.45 (DOI)000317475000038 ()978-1-4673-5165-2 (ISBN)
    Konferanse
    CSE 2012
    Prosjekter
    eSSENCEUPMARC
    Tilgjengelig fra: 2013-01-24 Laget: 2012-12-06 Sist oppdatert: 2018-01-16bibliografisk kontrollert
    2. DuctTeip: An efficient programming model for distributed task based parallel computing
    Åpne denne publikasjonen i ny fane eller vindu >>DuctTeip: An efficient programming model for distributed task based parallel computing
    2018 (engelsk)Inngår i: Computing Research Repository, nr 1801.03578Artikkel i tidsskrift (Annet vitenskapelig) Submitted
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-338832 (URN)
    Prosjekter
    UPMARCeSSENCE
    Tilgjengelig fra: 2018-01-10 Laget: 2018-01-14 Sist oppdatert: 2018-04-18bibliografisk kontrollert
    3. TaskUniVerse: A Task-Based Unified Interface for Versatile Parallel Execution
    Åpne denne publikasjonen i ny fane eller vindu >>TaskUniVerse: A Task-Based Unified Interface for Versatile Parallel Execution
    2018 (engelsk)Inngår i: Parallel Processing and Applied Mathematics: Part I, Springer, 2018, s. 169-184Konferansepaper, Publicerat paper (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Springer, 2018
    Serie
    Lecture Notes in Computer Science ; 10777
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-338836 (URN)10.1007/978-3-319-78024-5_16 (DOI)000458563300016 ()978-3-319-78023-8 (ISBN)
    Konferanse
    PPAM 2017
    Prosjekter
    eSSENCE
    Tilgjengelig fra: 2018-03-23 Laget: 2018-01-14 Sist oppdatert: 2019-03-14bibliografisk kontrollert
    4. Parallelization of hierarchical matrix algorithms for electromagnetic scattering problems
    Åpne denne publikasjonen i ny fane eller vindu >>Parallelization of hierarchical matrix algorithms for electromagnetic scattering problems
    Vise andre…
    2019 (engelsk)Inngår i: High-Performance Modelling and Simulation for Big Data Applications, Springer, 2019, s. 36-68Kapittel i bok, del av antologi (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Springer, 2019
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-338833 (URN)10.1007/978-3-030-16272-6_2 (DOI)978-3-030-16271-9 (ISBN)
    Prosjekter
    eSSENCE
    Tilgjengelig fra: 2019-03-26 Laget: 2018-01-14 Sist oppdatert: 2019-03-29bibliografisk kontrollert
    5. Distributed dynamic load balancing for task parallel programming
    Åpne denne publikasjonen i ny fane eller vindu >>Distributed dynamic load balancing for task parallel programming
    2018 (engelsk)Inngår i: Computing Research Repository, nr 1801.04582Artikkel i tidsskrift (Annet vitenskapelig) Submitted
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-338835 (URN)
    Prosjekter
    UPMARCeSSENCE
    Tilgjengelig fra: 2018-01-14 Laget: 2018-01-14 Sist oppdatert: 2018-04-18bibliografisk kontrollert
  • 252.
    Zak, Edvard
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Including Smartphone End User Apps in the Context of the Company Contact Center2014Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    Smartphones are becoming increasingly popular, with the result that customers prefer to carry out at least some customer services using an app on a mobile device. Among app users, smooth transfer to a live agent is seen as an important feature and this means that the company contact center need a solution to handle this as well as increasing numbers of interactions. The question this thesis tries to answer is "how can smartphone end user apps be included in the context of the company contact center"? To answer this question research was conducted regarding the possibilities of an Android smartphone, with the results of this research being used to define a use case, a state flow diagram and create a demonstration app. The thesis showed that it is possible to have an app as an online channel for customer service interactions. New possibilities in comparison to traditional telephony include that customer data such as topic, authentication, location and multimedia can be sent to the contact center before an actual interaction is started.

3456 251 - 252 of 252
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