Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Comparative Study on Two Different Direct Parallel Solution Strategies for Large-Scale Problems
Date
2009-04-08
Author
Bahcecioglu, T.
Ozmen, S.
Kurç, Özgür
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
186
views
0
downloads
Cite This
This paper presents a comparative study on two different direct parallel solution strategies for the linear solution of large scale actual finite element models: global and domain-by-domain. The global solution strategy was examined by utilizing the parallel multi-frontal equation solver, MUMPS [1], together with a finite element program. In a similar manner a substructure based parallel solution framework [2] was utilized for investigating the domain-by-domain strategy. Various large-scale structural models were solved with both solution strategies in order to illustrate the efficiencies and weaknesses of each solution strategy. The test runs were performed on a homogeneous PC cluster composed of eight computers connected with an ordinary 1 GBit network switch.
Subject Keywords
PC cluster
,
Large-scale
,
Substructure
,
Multi-frontal
,
Parallel solution
URI
https://hdl.handle.net/11511/54056
Collections
Department of Civil Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A generative model for multi class object recognition and detection
Ulusoy, İlkay (2006-01-01)
In this study, a generative type probabilistic model is proposed for object recognition. This model is trained by weakly labelled images and performs classification and detection at the same time. When test on highly challenging data sets, the model performs good for both tasks (classification and detection).
On Solving the Forward Kinematics of the 6-6 General Parallel Manipulator with an Efficient Evolutionary Algorithm
Rolland, Luc; Chandra, Rohitash (2010-07-08)
The G3-PCX genetic algorithm is compared with hybrid meta-heuristic approaches for solving the forward kinematics problem of the 6-6 general parallel manipulator. The G3-PCX shows improvements in terms of accuracy, response time and reliability. Several experiments confirm solving the given problem in less than 1 second. It also reports all the 16 unique real solutions which are verified by an exact algebraic method. This opens the way to simulation and certification applications.
A Unified approach for center-based clustering problems on networks
Eroğlu, Derya İpek; İyigün, Cem; Department of Industrial Engineering (2018)
In this thesis, Center-Based Clustering Problems on Networks are studied. Four different problems are considered differing in the assignment scheme of the data points and the objective function. Two different assignment schemes are considered, hard assignment and soft assignment. In hard assignment, data points (vertices) are strictly assigned to one cluster, while in soft assignment, vertices are assigned to the multiple clusters with a membership probability. Objective function of a clustering problem cou...
A Novel Parameter Identification Toolbox for the Selection of Hyperelastic Constitutive Models from Experimental Data
Dal, Hüsnü; Açıkgöz, Kemal (2017-10-13)
This paper presents a novel parameter identification toolbox based on various multi-objective optimization strategies for the selection of the best constitutive models from a given set of homogeneous experiments. The toolbox aims at providing an objective model selection procedure along with the material parameters for the rubber compound at hand. To this end, we utilize the multi-objective optimization using genetic algorithm of MATLAB. For the validation purposes, we use 10 constitutive laws.
A LINEAR MATHEMATICAL-MODEL FOR THE SEISMIC INPLANE BEHAVIOR OF BRICK MASONRY WALLS .2. DETERMINATION OF MODEL PARAMETERS THROUGH OPTIMIZATION USING EXPERIMENTAL-DATA
Sucuoğlu, Haluk; McNiven, Hugh (Wiley, 1984-01-01)
The parameters appearing in the mixture and effective modulus models proposed in Part 1 are determined through optimization by matching theoretical and experimental responses. The optimization analysis is performed in frequency space. The response quantities chosen to be matched are the complex frequency response functions (experimental and theoretical) relating the Fourier transforms of top and base accelerations of the wall. Computations in optimization analysis are carried out by introducing an object (e...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
T. Bahcecioglu, S. Ozmen, and Ö. Kurç, “A Comparative Study on Two Different Direct Parallel Solution Strategies for Large-Scale Problems,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54056.