Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Српски
  • Yкраї́нська
  • Log In
    New user? Click here to register. Have you forgotten your password?
Repository logo
  • Colleges, Institutes & Collections
  • Browse AAU-ETD
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Српски
  • Yкраї́нська
  • Log In
    New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Felleke, Lina"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • No Thumbnail Available
    Item
    Performance Improvement of Multi-Scale Modeling of Concrete Performance Solver Using Hybrid Cpu-Gpu System
    (Addis Ababa University, 2015-04) Felleke, Lina; Assamnew, Fitsum
    The multi-scale modeling of concrete performance solver is a tool developed at University of Tokyo. It is used to help engineers predict the material and structural properties of concrete structures under coupled mechanistic and environmental actions. The current implementation of multi-scale modeling of concrete performance solver is developed for Central Processing Unit (CPU) and CPU clusters and has longer runtimes. In this work, we present a CPU- Graphics Processing Unit (GPU) hybrid implementation of the tool. Changes were made to the LU factorization module by moving the computations to the GPU after profiling revealed it to be compute intensive. Tests conducted on the modified tool using real world sample concrete structure show that using the hybrid CPU-GPU implementation improved the performance by 35.29% on single node and 37.5% on cluster. Key Words:, Hybrid CPU-GPU system, General Purpose Computation on Graphics Processing Units, Multi frontal Massively Parallel Solver, Matrix Algebra on GPU and Multicore Architectures

Home |Privacy policy |End User Agreement |Send Feedback |Library Website

Addis Ababa University © 2023