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Scientific computing on hybrid architectures
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.
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modern computer architectures, with multicore CPUs and GPUs or other accelerators, make stronger demands than ever on writers of scientific code. As a rule of thumb, the fastest, most efficient program consists of labor-intensive code written by expert programmers for a certain application on a particular computer. This thesis deals with several algorithmic and technical approaches towards effectively satisfying the demand for high-performance parallel programming without incurring such a high cost in expert programmer time. Effective programming is accomplished by writing performance-portable code where performance-critical functionality is provided either by external software or at least a balance between maintainability/generality and efficiency.
Place, publisher, year, edition, pages
Uppsala University, 2013.
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2013-002
National Category
Computer Sciences Computational Mathematics
Research subject
Scientific Computing
Identifiers
URN: urn:nbn:se:uu:diva-200242OAI: oai:DiVA.org:uu-200242DiVA, id: diva2:622836
Supervisors
Projects
UPMARCeSSENCE
Available from: 2013-05-31 Created: 2013-05-23 Last updated: 2018-01-11Bibliographically approved
List of papers
1. Efficiently implementing Monte Carlo electrostatics simulations on multicore accelerators
Open this publication in new window or tab >>Efficiently implementing Monte Carlo electrostatics simulations on multicore accelerators
2012 (English)In: Applied Parallel and Scientific Computing: Part II, Berlin: Springer-Verlag , 2012, p. 379-388Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2012
Series
Lecture Notes in Computer Science ; 7134
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-135987 (URN)10.1007/978-3-642-28145-7_37 (DOI)000309716000037 ()978-3-642-28144-0 (ISBN)
Conference
PARA 2010: State of the Art in Scientific and Parallel Computing
Projects
eSSENCEUPMARC
Available from: 2012-02-16 Created: 2010-12-09 Last updated: 2018-01-12Bibliographically approved
2. A simple model for tuning tasks
Open this publication in new window or tab >>A simple model for tuning tasks
2011 (English)In: Proc. 4th Swedish Workshop on Multi-Core Computing, Linköping, Sweden: Linköping University , 2011, p. 45-49Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Linköping, Sweden: Linköping University, 2011
National Category
Software Engineering
Identifiers
urn:nbn:se:uu:diva-162609 (URN)
Conference
MCC11
Projects
UPMARCeSSENCE
Available from: 2011-11-24 Created: 2011-12-02 Last updated: 2018-01-12Bibliographically approved
3. Parallel implementation of the Sherman–Morrison matrix inverse algorithm
Open this publication in new window or tab >>Parallel implementation of the Sherman–Morrison matrix inverse algorithm
2013 (English)In: Applied Parallel and Scientific Computing, Berlin: Springer-Verlag , 2013, p. 206-219Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Berlin: Springer-Verlag, 2013
Series
Lecture Notes in Computer Science ; 7782
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-198520 (URN)10.1007/978-3-642-36803-5_15 (DOI)000343867800015 ()978-3-642-36802-8 (ISBN)
Conference
PARA 2012: State of the Art in Scientific and Parallel Computing
Projects
UPMARCeSSENCE
Available from: 2013-02-18 Created: 2013-04-17 Last updated: 2018-01-11Bibliographically approved
4. Dynamic autotuning of adaptive fast multipole methods on hybrid multicore CPU and GPU systems
Open this publication in new window or tab >>Dynamic autotuning of adaptive fast multipole methods on hybrid multicore CPU and GPU systems
2014 (English)In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 36, p. C376-C399Article in journal (Refereed) Published
National Category
Computer Sciences Computational Mathematics Energy Engineering
Identifiers
urn:nbn:se:uu:diva-200240 (URN)10.1137/130943595 (DOI)000344743800040 ()
Projects
eSSENCEUPMARC
Available from: 2014-08-29 Created: 2013-05-23 Last updated: 2018-01-11Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
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  • en-GB
  • en-US
  • fi-FI
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  • nn-NB
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  • Other locale
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Output format
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