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  • 1. Abel, John H.
    et al.
    Drawert, Brian
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Petzold, Linda R.
    GillesPy: A Python package for stochastic model building and simulation2016In: IEEE Life Sciences Letters, E-ISSN 2332-7685, Vol. 2, p. 35-38Article in journal (Refereed)
  • 2. Ahmed, Laeeq
    et al.
    Georgiev, Valentin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Capuccini, Marco
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Schaal, Wesley
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Laure, Erwin
    Spjuth, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Efficient iterative virtual screening with Apache Spark and conformal prediction2018In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 10, article id 8Article in journal (Refereed)
  • 3.
    Andrejev, Andrej
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Holmgren, Sverker
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Risch, Tore
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Scientific analysis by queries in extended SPARQL over a scalable e-Science data store2013In: Proc. 9th International Conference on e-Science, Los Alamitos, CA: IEEE Computer Society, 2013, p. 98-106Conference paper (Refereed)
  • 4. Antolín, Roberto
    et al.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Gorjanc, Gregor
    Money, Daniel
    Hickey, John M.
    A hybrid method for the imputation of genomic data in livestock populations2017In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 49, article id 30Article in journal (Refereed)
  • 5. Anzt, Hartwig
    et al.
    Lukarski, Dimitar
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Tomov, Stanimire
    Dongarra, Jack
    Self-adaptive multiprecision preconditioners on multicore and manycore architectures2015In: High Performance Computing for Computational Science – VECPAR 2014, Springer, 2015, p. 115-123Conference paper (Refereed)
  • 6. Appleton, Owen
    et al.
    Cameron, David
    Cernák, Jozef
    Dóbé, Péter
    Ellert, Mattias
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Frågåt, Thomas
    Grønager, Michael
    Johansson, Daniel
    Jönemo, Johan
    Kleist, Josva
    Kocan, Marek
    Konstantinov, Aleksandr
    Kónya, Balázs
    Márton, Iván
    Mohn, Bjarte
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Möller, Steffen
    Müller, Henning
    Nagy, Zsombor
    Nilsen, Jon K.
    Ould-Saada, Farid
    Pajchel, Katarina
    Qiang, Weizhong
    Read, Alexander
    Rosendahl, Peter
    Röczei, Gábor
    Savko, Martin
    Skou Andersen, Martin
    Smirnova, Oxana
    Stefán, Péter
    Szalai, Ferenc
    Taga, Adrian
    Toor, Salman Z.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Wäänänen, Anders
    Zhou, Xin
    The next-generation ARC middleware2010In: Annales des télécommunications, ISSN 0003-4347, E-ISSN 1958-9395, Vol. 65, p. 771-776Article in journal (Refereed)
  • 7. Arjmand, Doghonay
    et al.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Kreiss, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Temporal upscaling in micromagnetism via heterogeneous multiscale methods2019In: Journal of Computational and Applied Mathematics, ISSN 0377-0427, E-ISSN 1879-1778, Vol. 345, p. 99-113Article in journal (Refereed)
  • 8.
    Artemov, Anton G.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Inverse factorization in electronic structure theory: Analysis and parallelization2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This licentiate thesis is a part of an effort to run large electronic structure calculations in modern computational environments with distributed memory. The ultimate goal is to model materials consisting of millions of atoms at the level of quantum mechanics. In particular, the thesis focuses on different aspects of a computational problem of inverse factorization of Hermitian positive definite matrices. The considered aspects are numerical properties of the algorithms and parallelization. Not only is an efficient and scalable computation of inverse factors necessary in order to be able to run large scale electronic computations based on the Hartree–Fock or Kohn–Sham approaches with the self-consistent field procedure, but it can be applied more generally for preconditioner construction.

    Parallelization of algorithms with unknown load and data distributions requires a paradigm shift in programming. In this thesis we also discuss a few parallel programming models with focus on task-based models, and, more specifically, the Chunks and Tasks model.

    List of papers
    1. Localized inverse factorization
    Open this publication in new window or tab >>Localized inverse factorization
    2018 (English)In: Computing Research Repository, no 1812.04919Article in journal (Other academic) Submitted
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-381327 (URN)
    Projects
    eSSENCE
    Available from: 2018-12-12 Created: 2019-04-08 Last updated: 2019-09-20Bibliographically approved
    2. Parallelization and scalability analysis of inverse factorization using the chunks and tasks programming model
    Open this publication in new window or tab >>Parallelization and scalability analysis of inverse factorization using the chunks and tasks programming model
    2019 (English)In: Parallel Computing, ISSN 0167-8191, E-ISSN 1872-7336, Vol. 89, article id 102548Article in journal (Refereed) Published
    National Category
    Computational Mathematics Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-381329 (URN)10.1016/j.parco.2019.102548 (DOI)
    Projects
    eSSENCE
    Available from: 2019-09-02 Created: 2019-04-08 Last updated: 2019-09-24Bibliographically approved
  • 9.
    Artemov, Anton G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Rudberg, Elias
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Rubensson, Emanuel H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Parallelization and scalability analysis of inverse factorization using the chunks and tasks programming model2019In: Parallel Computing, ISSN 0167-8191, E-ISSN 1872-7336, Vol. 89, article id 102548Article in journal (Refereed)
  • 10.
    Ausmees, Kristiina
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    John, Aji
    Toor, Salman Z.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data2018In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 19, p. 240:1-11, article id 240Article in journal (Refereed)
  • 11.
    Bauer, Pavol
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Parallelism and efficiency in discrete-event simulation2015Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Discrete-event models depict systems where a discrete state is repeatedly altered by instantaneous changes in time, the events of the model. Such models have gained popularity in fields such as Computational Systems Biology or Computational Epidemiology due to the high modeling flexibility and the possibility to easily combine stochastic and deterministic dynamics. However, the system size of modern discrete-event models is growing and/or they need to be simulated at long time periods. Thus, efficient simulation algorithms are required, as well as the possibility to harness the compute potential of modern multicore computers. Due to the sequential design of simulators, parallelization of discrete event simulations is not trivial. This thesis discusses event-based modeling and sensitivity analysis and also examines ways to increase the efficiency of discrete-event simulations and to scale models involving deterministic and stochastic spatial dynamics on a large number of processor cores.

    List of papers
    1. Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics
    Open this publication in new window or tab >>Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics
    2015 (English)In: Numerical Mathematics and Advanced Applications: ENUMATH 2013, Springer, 2015, p. 519-527Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Springer, 2015
    Series
    Lecture Notes in Computational Science and Engineering ; 103
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-237184 (URN)10.1007/978-3-319-10705-9_51 (DOI)978-3-319-10704-2 (ISBN)
    Conference
    ENUMATH 2013
    Projects
    eSSENCEUPMARC
    Available from: 2014-10-31 Created: 2014-11-28 Last updated: 2018-11-12Bibliographically approved
    2. Fast event-based epidemiological simulations on national scales
    Open this publication in new window or tab >>Fast event-based epidemiological simulations on national scales
    2016 (English)In: The international journal of high performance computing applications, ISSN 1094-3420, E-ISSN 1741-2846, Vol. 30, p. 438-453Article in journal (Refereed) Published
    National Category
    Computer Sciences Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-264751 (URN)10.1177/1094342016635723 (DOI)000387763100005 ()
    Projects
    UPMARCeSSENCE
    Available from: 2016-04-11 Created: 2015-10-16 Last updated: 2018-11-12Bibliographically approved
    3. Efficient inter-process synchronization for parallel discrete event simulation on multicores
    Open this publication in new window or tab >>Efficient inter-process synchronization for parallel discrete event simulation on multicores
    2015 (English)In: Proc. 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, New York: ACM Press, 2015, p. 183-194Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    New York: ACM Press, 2015
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-260199 (URN)10.1145/2769458.2769476 (DOI)978-1-4503-3583-6 (ISBN)
    Conference
    SIGSIM-PADS 2015
    Projects
    UPMARC
    Available from: 2015-06-10 Created: 2015-08-17 Last updated: 2018-11-12Bibliographically approved
  • 12.
    Bauer, Pavol
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Parallelism in Event-Based Computations with Applications in Biology2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Event-based models find frequent usage in fields such as computational physics and biology as they may contain both continuous and discrete state variables and may incorporate both deterministic and stochastic state transitions. If the state transitions are stochastic, computer-generated random numbers are used to obtain the model solution. This type of event-based computations is also known as Monte-Carlo simulation.

    In this thesis, I study different approaches to execute event-based computations on parallel computers. This ultimately allows users to retrieve their simulation results in a fraction of the original computation time. As system sizes grow continuously or models have to be simulated at longer time scales, this is a necessary approach for current computational tasks.

    More specifically, I propose several ways to asynchronously simulate such models on parallel shared-memory computers, for example using parallel discrete-event simulation or task-based computing. The particular event-based models studied herein find applications in systems biology, computational epidemiology and computational neuroscience.

    In the presented studies, the proposed methods allow for high efficiency of the parallel simulation, typically scaling well with the number of used computer cores. As the scaling typically depends on individual model properties, the studies also investigate which quantities have the greatest impact on the simulation performance.

    Finally, the presented studies include other insights into event-based computations, such as methods how to estimate parameter sensitivity in stochastic models and how to simulate models that include both deterministic and stochastic state transitions.

    List of papers
    1. Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics
    Open this publication in new window or tab >>Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics
    2015 (English)In: Numerical Mathematics and Advanced Applications: ENUMATH 2013, Springer, 2015, p. 519-527Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Springer, 2015
    Series
    Lecture Notes in Computational Science and Engineering ; 103
    National Category
    Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-237184 (URN)10.1007/978-3-319-10705-9_51 (DOI)978-3-319-10704-2 (ISBN)
    Conference
    ENUMATH 2013
    Projects
    eSSENCEUPMARC
    Available from: 2014-10-31 Created: 2014-11-28 Last updated: 2018-11-12Bibliographically approved
    2. Multiscale modelling via split-step methods in neural firing
    Open this publication in new window or tab >>Multiscale modelling via split-step methods in neural firing
    2018 (English)In: Mathematical and Computer Modelling of Dynamical Systems, ISSN 1387-3954, E-ISSN 1744-5051, Vol. 24, p. 426-445Article in journal (Refereed) Published
    National Category
    Computational Mathematics Neurosciences
    Identifiers
    urn:nbn:se:uu:diva-332008 (URN)10.1080/13873954.2018.1488740 (DOI)000440605300005 ()
    Projects
    UPMARCeSSENCE
    Available from: 2018-08-01 Created: 2017-10-22 Last updated: 2018-11-19Bibliographically approved
    3. Fast event-based epidemiological simulations on national scales
    Open this publication in new window or tab >>Fast event-based epidemiological simulations on national scales
    2016 (English)In: The international journal of high performance computing applications, ISSN 1094-3420, E-ISSN 1741-2846, Vol. 30, p. 438-453Article in journal (Refereed) Published
    National Category
    Computer Sciences Computational Mathematics
    Identifiers
    urn:nbn:se:uu:diva-264751 (URN)10.1177/1094342016635723 (DOI)000387763100005 ()
    Projects
    UPMARCeSSENCE
    Available from: 2016-04-11 Created: 2015-10-16 Last updated: 2018-11-12Bibliographically approved
    4. Efficient inter-process synchronization for parallel discrete event simulation on multicores
    Open this publication in new window or tab >>Efficient inter-process synchronization for parallel discrete event simulation on multicores
    2015 (English)In: Proc. 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, New York: ACM Press, 2015, p. 183-194Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    New York: ACM Press, 2015
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-260199 (URN)10.1145/2769458.2769476 (DOI)978-1-4503-3583-6 (ISBN)
    Conference
    SIGSIM-PADS 2015
    Projects
    UPMARC
    Available from: 2015-06-10 Created: 2015-08-17 Last updated: 2018-11-12Bibliographically approved
    5. Exposing inter-process information for efficient parallel discrete event simulation of spatial stochastic systems
    Open this publication in new window or tab >>Exposing inter-process information for efficient parallel discrete event simulation of spatial stochastic systems
    2017 (English)In: Proc. 5th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, New York: ACM Press, 2017, p. 53-64Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    New York: ACM Press, 2017
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-328367 (URN)10.1145/3064911.3064916 (DOI)978-1-4503-4489-0 (ISBN)
    Conference
    SIGSIM-PADS 2017
    Projects
    UPMARC
    Available from: 2017-05-16 Created: 2017-08-22 Last updated: 2018-11-12Bibliographically approved
  • 13.
    Bauer, Pavol
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Sensitivity estimation and inverse problems in spatial stochastic models of chemical kinetics2015In: Numerical Mathematics and Advanced Applications: ENUMATH 2013, Springer, 2015, p. 519-527Conference paper (Refereed)
  • 14.
    Bauer, Pavol
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Mikulovic, Sanja
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Developmental Genetics.
    Senek, Aleksandar
    Multiscale modelling via split-step methods in neural firing2018In: Mathematical and Computer Modelling of Dynamical Systems, ISSN 1387-3954, E-ISSN 1744-5051, Vol. 24, p. 426-445Article in journal (Refereed)
  • 15.
    Bauer, Pavol
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Widgren, Stefan
    Fast event-based epidemiological simulations on national scales2016In: The international journal of high performance computing applications, ISSN 1094-3420, E-ISSN 1741-2846, Vol. 30, p. 438-453Article in journal (Refereed)
  • 16.
    Bauer, Pavol
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Lindén, Jonatan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Jonsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Efficient inter-process synchronization for parallel discrete event simulation on multicores2015In: Proc. 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, New York: ACM Press, 2015, p. 183-194Conference paper (Refereed)
  • 17. Benchaib, Mohamed Amine
    et al.
    Bouchnita, Anass
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Volpert, Vitaly
    Makhoute, Abdelkader
    Mathematical modeling reveals that the administration of EGF can promote the elimination of lymph node metastases by PD-1/PD-L1 blockade2019In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 7, article id 104Article in journal (Refereed)
  • 18.
    Berglund, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Eckerdal, Anna
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Learning practice and theory in programming education: Students’ lived experience2015In: Proc. 3rd International Conference on Learning and Teaching in Computing and Engineering, Los Alamitos, CA: IEEE Computer Society, 2015, p. 180-186Conference paper (Refereed)
  • 19.
    Berglund, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Eckerdal, Anna
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Learning to program: A discussion on the interplay of theory and practice2015In: Proc. 1st Al Baha University and Uppsala University Symposium on Quality in Computing Education, 2015, p. 16-18Conference paper (Refereed)
  • 20.
    Blamey, Ben
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Wrede, Fredrik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Karlsson, Johan
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Toor, Salman
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Adapting the secretary hiring problem for optimal hot–cold tier placement under top-K workloads2019In: Proc. 19th International Symposium on Cluster, Cloud, and Grid Computing, Los Alamitos, CA: IEEE Computer Society, 2019, p. 576-583Conference paper (Refereed)
  • 21.
    Blanc, Emilie
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Mesoscopic modeling of stochastic reaction–diffusion kinetics in the subdiffusive regime2016In: Multiscale Modeling & simulation, ISSN 1540-3459, E-ISSN 1540-3467, Vol. 14, p. 668-707Article in journal (Refereed)
  • 22.
    Bouchnita, Anass
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    A 3D multiscale model to explore the role of EGFR overexpression in tumourigenesis2019In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 81, p. 2323-2344Article in journal (Refereed)
  • 23.
    Bouchnita, Anass
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Volpert, Vitaly
    A multiscale model of platelet-fibrin thrombus growth in the flow2019In: Computers & Fluids, ISSN 0045-7930, E-ISSN 1879-0747, Vol. 184, p. 10-20Article in journal (Refereed)
  • 24. Boustedt, Jonas
    et al.
    Eckerdal, Anna
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    McCartney, Robert
    Sanders, Kate
    Thomas, Lynda
    Zander, Carol
    Students' perceptions of the differences between formal and informal learning2011In: Proc. 7th International Computing Education Research Workshop, New York: ACM Press , 2011, p. 61-68Conference paper (Refereed)
  • 25. Brumm, Bernd
    et al.
    Kieri, Emil
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    A matrix-free Legendre spectral method for initial–boundary value problems2016In: Electronic Transactions on Numerical Analysis, ISSN 1068-9613, E-ISSN 1068-9613, Vol. 45, p. 283-304Article in journal (Refereed)
  • 26.
    Bull, Jonathan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Holmgren, Sverker
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    A direct solver for the advection–diffusion equation using Green's functions and low-rank approximation2016In: Proc. 7th ECCOMAS Congress, European Community on Computional Methods in Applied Sciences (ECCOMAS), 2016, p. 7302-7316Conference paper (Refereed)
  • 27.
    Capuccini, Marco
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Enabling Scalable Data Analysis on Cloud Resources with Applications in Life Science2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Over the past 20 years, the rise of high-throughput methods in life science has enabled research laboratories to produce massive datasets of biological interest. When dealing with this "data deluge" of modern biology researchers encounter two major challenges: first, there is a need for substantial technical skills for dealing with Big Data and; second, infrastructure procurement becomes difficult. In connection to this second challenge, the computing model and business trend that was originally popularized by Amazon under the name of cloud computing represents an interesting opportunity. Instead of buying computing infrastructure upfront, cloud providers enable the allocation and release of virtual resources on-demand. These resources are then billed with a pay-per-use pricing model and physical infrastructure management is delegated to the provider. In this thesis, we introduce a number of methods for running Big Data analyses of biological interest using cloud computing. Considerable efforts were made in enabling the application of trusted, bioinformatics software to Big Data scenarios as opposed to reimplementing the existing codebase. Further, we improve the accessibility of the technology with the aim of reducing the entry barrier for biologists. The thesis includes 5 papers. In Papers I and II, we explore the applicability of Apache Spark, one of the leading Big Data analytics platforms in cloud environments, to two drug-discovery use cases. In Paper III, we present a general method for running bioinformatics analyses on the cloud using the microservices-oriented architecture. In Paper IV, we introduce a method that combines microservices and Apache Spark with the aim of providing the best of both technologies. In Paper V, we discuss how to reduce the entry barrier for the allocation of cloud research environments. We show that all of the developed methods scale well and we provide high-level programming interfaces for improving accessibility. We have also made the developed software publicly available.

    List of papers
    1. Conformal prediction in Spark: Large-scale machine learning with confidence
    Open this publication in new window or tab >>Conformal prediction in Spark: Large-scale machine learning with confidence
    2015 (English)In: Proc. 2nd International Symposium on Big Data Computing, Los Alamitos, CA: IEEE Computer Society, 2015, p. 61-67Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Los Alamitos, CA: IEEE Computer Society, 2015
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-283636 (URN)10.1109/BDC.2015.35 (DOI)000380459200007 ()978-0-7695-5696-3 (ISBN)
    Conference
    BDC 2015, December 7–10, Limassol, Cyprus
    Projects
    eSSENCE
    Available from: 2015-12-10 Created: 2016-04-13 Last updated: 2019-08-22Bibliographically approved
    2. Large-scale virtual screening on public cloud resources with Apache Spark
    Open this publication in new window or tab >>Large-scale virtual screening on public cloud resources with Apache Spark
    Show others...
    2017 (English)In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 9, article id 15Article in journal (Refereed) Published
    National Category
    Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-318693 (URN)10.1186/s13321-017-0204-4 (DOI)000396830300001 ()28316653 (PubMedID)
    Projects
    eSSENCE
    Available from: 2017-03-06 Created: 2017-03-27 Last updated: 2019-09-30Bibliographically approved
    3. Interoperable and scalable data analysis with microservices: Applications in metabolomics
    Open this publication in new window or tab >>Interoperable and scalable data analysis with microservices: Applications in metabolomics
    Show others...
    2019 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 35, no 19, p. 3752-3760Article in journal (Refereed) Published
    National Category
    Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-390670 (URN)10.1093/bioinformatics/btz160 (DOI)
    Available from: 2019-03-09 Created: 2019-08-13 Last updated: 2019-10-14Bibliographically approved
    4. MaRe: a MapReduce-Oriented Framework for Processing Big Data with Application Containers
    Open this publication in new window or tab >>MaRe: a MapReduce-Oriented Framework for Processing Big Data with Application Containers
    2018 (English)Manuscript (preprint) (Other academic)
    National Category
    Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-390664 (URN)
    Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-22
    5. On-Demand Virtual Research Environments using Microservices
    Open this publication in new window or tab >>On-Demand Virtual Research Environments using Microservices
    Show others...
    2018 (English)Manuscript (preprint) (Other academic)
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:uu:diva-390665 (URN)
    Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-22
  • 28.
    Capuccini, Marco
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Ahmed, Laeeq
    Schaal, Wesley
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Laure, Erwin
    Spjuth, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Large-scale virtual screening on public cloud resources with Apache Spark2017In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 9, article id 15Article in journal (Refereed)
  • 29.
    Capuccini, Marco
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Carlsson, Lars
    Norinder, Ulf
    Spjuth, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Conformal prediction in Spark: Large-scale machine learning with confidence2015In: Proc. 2nd International Symposium on Big Data Computing, Los Alamitos, CA: IEEE Computer Society, 2015, p. 61-67Conference paper (Refereed)
  • 30. Caulfield, Emmet
    et al.
    Hellander, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    CellMC: a multiplatform model compiler for the Cell Broadband Engine and x862010In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 26, p. 426-428Article in journal (Refereed)
  • 31. Chevallier, Augustin
    et al.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Pathwise error bounds in multiscale variable splitting methods for spatial stochastic kinetics2018In: SIAM Journal on Numerical Analysis, ISSN 0036-1429, E-ISSN 1095-7170, Vol. 56, p. 469-498Article in journal (Refereed)
  • 32.
    Christoffer, Zakrisson
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Effektiva lösningsmetoder för Schrödingerekvationen: En jämförelse2013Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In this paper the rate of convergence, speed of execution and symplectic properties of the time-integrators Leap-Frog (LF2), fourth order Runge-Kutta(RK4) and Crank-Nicholson (CN2) have been studied. This was done by solving the one-dimensional model for a particle in a box (Dirichlet-conditions). The results show that RK4 is the fastest in achieving higher tolerances, while CN2 is the fastest in achieving lower tolerances. Fourth order corrections of LF (LF4)and CN (CN4) were also studied, though these showed no improvements overLF2 and CN2. All methods were shown to exhibit symplectic behavior.

  • 33.
    Christoffersson, Gustaf
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    Lomei, Jalal
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    O'Callaghan, Paul
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    Kreuger, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    Engblom, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Phillipson, Mia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    Vascular sprouts induce local attraction of proangiogenic neutrophils2017In: Journal of Leukocyte Biology, ISSN 0741-5400, E-ISSN 1938-3673, Vol. 102, p. 741-751Article in journal (Refereed)
  • 34. Clear, Tony
    et al.
    Whalley, Jacqueline
    Robbins, Phil