• About
  • Policies
  • What is open access
  • 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.

      The effect of various sparsity structures on parallelism and algorithms to reveal those structures

      Thumbnail
      View / Download
      262.7 Kb
      Author(s)
      Selvitopi, O.
      Acer, S.
      Manguoğlu, M.
      Aykanat, Cevdet
      Date
      2020
      Source Title
      Modeling and Simulation in Science, Engineering and Technology
      Print ISSN
      2164-3679
      Electronic ISSN
      2164-3725
      Publisher
      Birkhauser
      Pages
      35 - 62
      Language
      English
      Type
      Book Chapter
      Item Usage Stats
      129
      views
      52
      downloads
      Book Title
      Parallel algorithms in computational science and engineering
      Series
      Modeling and Simulation in Science, Engineering and Technology
      Abstract
      Structured sparse matrices can greatly benefit parallel numerical methods in terms of parallel performance and convergence. In this chapter, we present combinatorial models for obtaining several different sparse matrix forms. There are four basic forms we focus on: singly-bordered block-diagonal form, doubly-bordered block-diagonal form, nonempty off-diagonal block minimization, and block diagonal with overlap form. For each of these forms, we first present the form in detail and describe what goals are sought within the form, and then examine the combinatorial models that attain the respective form while targeting the sought goals, and finally explain in which aspects the forms benefit certain parallel numerical methods and their relationship with the models. Our work focuses especially on graph and hypergraph partitioning models in obtaining the mentioned forms. Despite their relatively high preprocessing overhead compared to other heuristics, they have proven to model the given problem more accurately and this overhead can be often amortized due the fact that matrix structure does not change much during a typical numerical simulation. This chapter presents a number of models and their relationship with parallel numerical methods.
      Permalink
      http://hdl.handle.net/11693/75792
      Published Version (Please cite this version)
      https://dx.doi.org/10.1007/978-3-030-43736-7_2
      https://doi.org/10.1007/978-3-030-43736-7
      Collections
      • Department of Computer Engineering 1561
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsCoursesThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsCourses

      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 User and Access Services. Phone: (312) 290 1298
      © Bilkent University - Library IT

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