• About
  • Policies
  • What is openaccess
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Algorithms for efficient vectorization of repeated sparse power system network computations

      Thumbnail
      View / Download
      946.3 Kb
      Author
      Aykanat, Cevdet
      Özgü, Ö.
      Güven, N.
      Date
      1995
      Source Title
      IEEE Transactions on Power Systems
      Print ISSN
      0885-8950
      Electronic ISSN
      1558-0679
      Publisher
      IEEE
      Volume
      10
      Issue
      1
      Pages
      448 - 456
      Language
      English
      Type
      Article
      Item Usage Stats
      135
      views
      86
      downloads
      Abstract
      Standard sparsity-based algorithms used in power system appllcations need to be restructured for efficient vectorization due to the extremely short vectors processed. Further, intrinsic architectural features of vector computers such as chaining and sectioning should also be exploited for utmost performance. This paper presents novel data storage schemes and vectorization alsorim that resolve the recurrence problem, exploit chaining and minimize the number of indirect element selections in the repeated solution of sparse linear system of equations widely encountered in various power system problems. The proposed schemes are also applied and experimented for the vectorization of power mismatch calculations arising in the solution phase of FDLF which involves typical repeated sparse power network computations. The relative performances of the proposed and existing vectorization schemes are evaluated, both theoretically and experimentally on IBM 3090ArF.
      Keywords
      Algorithms
      Calculations
      Computer Architecture
      Computer Hardware
      Data Storage Equipment
      Data Structures
      Electric Load Flow
      Fortran (Programming Language)
      Optimization
      Parallel Processing Systems
      Pipeline Processing Systems
      Vectors Efficient Vectorization
      Fast Decoupled Load Flow
      Forward/backward Substitution
      Sparse Linear System
      Sparse Power System Network
      Vector Processing
      Electric Power Systems
      Vector Computers
      Matrix
      Factorization
      Flow
      Permalink
      http://hdl.handle.net/11693/10801
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/59.373970
      Collections
      • Department of Computer Engineering 1368
      Show full item record

      Related items

      Showing items related by title, author, creator and subject.

      • Thumbnail

        BilKristal 4.0: A tool for crystal parameters extraction and defect quantification 

        Okuyan, E.; Okuyan, C. (Elsevier, 2015)
        In this paper, we present a revised version of BilKristal 3.0 tool. Raycast screenshot functionality is added to provide improved visual analysis. We added atomic distance analysis functionality to assess crystalline ...
      • Thumbnail

        A tool for pattern information extraction and defect quantification from crystal structures 

        Okuyan, E.; Okuyan, E. (Elsevier, 2015)
        In this paper, we present a revised version of BilKristal 2.0 tool. We added defect quantification functionality to assess crystalline defects. We improved visualization capabilities by adding transparency support and ...
      • Thumbnail

        On compact solution vectors in Kronecker-based Markovian analysis 

        Buchholz, P.; Dayar T.; Kriege, J.; Orhan, M. C. (Elsevier, 2017)
        State based analysis of stochastic models for performance and dependability often requires the computation of the stationary distribution of a multidimensional continuous-time Markov chain (CTMC). The infinitesimal generator ...

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      Copyright © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy