A Comparative Study on Two Different Direct Parallel Solution Strategies for Large-Scale Problems

2009-04-08
Bahcecioglu, T.
Ozmen, S.
Kurç, Özgür
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.

Suggestions

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).
A Methodology for Resolution Mapping for Cross-Resolution Simulation using Event-B
Kara, Ahmet; Oğuztüzün, Mehmet Halit S.; Alpdemir, M. Nedim (2015-11-01)
This paper proposes a software engineering solution for implementing simulations via the composition of models at different resolution levels with the help of formal methods. Our solution provides a systematic methodology that offers a well-defined sequence of stages to obtain executable converters for entity resolution mapping, given the types of entity attributes that are exchanged at model interfaces and the mapping specifications. Our methodology uses Event-B as the formal specification language and Dis...
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 procedure on ground motion selection and scaling for nonlinear response of simple structural systems
Ay, Bekir Özer (2012-10-01)
This study presents a ground-motion selection and scaling methodology that preserves the basic seismological features of the scaled records with reduced scatter in the nonlinear structural response. The methodology modifies each strong-motion recording with known fundamental seismological parameters using the estimations of ground-motion prediction equations for a given target hazard level. It provides robust estimations on target building response through scaled ground motions and calculates the dispersion...
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.
Citation Formats
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.