350 research outputs found
Scalability Analysis of Parallel GMRES Implementations
Applications involving large sparse nonsymmetric linear systems encourage parallel implementations of robust iterative solution methods, such as GMRES(k). Two parallel versions of GMRES(k) based on different data distributions and using Householder reflections in the orthogonalization phase, and variations of these which adapt the restart value k, are analyzed with respect to scalability (their ability to maintain fixed efficiency with an increase in problem size and number of processors).A theoretical algorithm-machine model for scalability is derived and validated by experiments on three parallel computers, each with different machine characteristics
A comparison of three Algorithms for Tracing Nonlinear Equilibrium Paths of Structural Systems
The relative efficiencies of the Riks/Wempner, CrisïŹeld, and normal flow solution algorithms for tracking nonlinear equilibrium paths of structural systems are compared. It is argued that the normal flow algorithm maybe both more computationally efficient and more robust compared to the other two algorithms when tracing the path through severe nonlinearities such as those associated with structural collapse. This is demonstrated qualitatively by comparing the relative behaviors of each algorithm in the vicinity of a severe nonlinearity. Quantitative results are presented for the collapse a blade stiffened panel
Structural Design using Cellular Automata
Traditional parallel methods for structural design do not scale well. This paper discusses the application of massively scalable cellular automata (CA) techniques to structural design. There are two sets of CA rules, one used to propagate stresses and strains, and one to perform design analysis. These rules can be applied serially,periodically,or concurrently, and Jacobi or Gauss-
Seidel style updating can be done. These options are compared with respect to convergence,speed, and stability
Polynomial Response Surface Approximations for the Multidisciplinary Design Optimization of a High Speed Civil Transport
Surrogate functions have become an important tool in multidisciplinary design optimization to deal with noisy functions, high computational cost, and the practical difficulty of integrating legacy disciplinary computer codes. A combination of mathematical, statistical, and engineering techniques, well known in other contexts, have made polynomial surrogate functions viable for MDO. Despite the obvious limitations imposed by sparse high fidelity data in high dimensions and the locality of low order polynomial approximations, the success of the panoply of techniques based on polynomial response surface approximations for MDO shows that the implementation details are more important than the underlying approximation method (polynomial, spline, DACE, kernel regression, etc.). This paper surveys some of the ancillary techniquesâstatistics, global search, parallel computing, variable complexity modelingâthat augment the construction and use of polynomial surrogates
Data Driven Surrogate Based Optimization in the Problem Solving Environment WBCSim
Large scale, multidisciplinary, engineering designs are always difficult due to the complexity and dimensionality of these problems. Direct coupling between the analysis codes and the optimization routines can be prohibitively time consuming due to the complexity of the underlying simulation codes. One way of tackling this problem is by constructing computationally cheap(er) approximations of the expensive simulations, that mimic the behavior of the simulation model as closely as possible. This paper presents a data driven, surrogate based optimization algorithm that uses a trust region based sequential approximate optimization (SAO) framework and a statistical sampling approach based on design of experiment (DOE) arrays. The algorithm is implemented using techniques from two packagesâSURFPACK and SHEPPACK that provide a collection of approximation algorithms to build the surrogates and three different DOE techniquesâfull factorial (FF), Latin hypercube sampling (LHS), and central composite design (CCD)âare used to train the surrogates. The results are compared with the optimization results obtained by directly coupling an optimizer with the simulation code. The biggest concern in using the SAO framework based on statistical sampling is the generation of the required database. As the number of design variables grows, the computational cost of generating the required database grows rapidly. A data driven approach is proposed to tackle this situation, where the trick is to run the expensive simulation if and only if a nearby data point does not exist in the cumulatively growing database. Over time the database matures and is enriched as more and more optimizations are performed. Results show that the proposed methodology dramatically reduces the total number of calls to the expensive simulation runs during the optimization process
A Domain Decomposition Preconditioner for Hermite Collocation Problems
We propose a preconditioning method for linear systems of equations arising from piecewise Hermite bicubic collocation applied to two dimensional elliptic PDEs with mixed boundary conditions. We construct an efficient, parallel preconditioner for the GMRES method. The main contribution of the paper is a novel interface preconditioner derived in the framework of substructuring and employing a local Hermite collocation discretization for the interface subproblems based on a hybrid fine-coarse mesh. Interface equations based on this mesh depend only weakly on unknowns associated with subdomains. The effectiveness of the proposed method is highlighted by numerical experiments that cover a variety of problems
Photoluminescence and phonon satellites of single InGaN/GaN quantum wells with varying GaN cap thickness
Variations in thickness of the GaN caps above single InGaN quantum wells have been studied using photoluminescence spectroscopy. Data are presented from two series of samples designed to promote energy transfer to luminescent species on the surface. Improvements in the optical properties as the GaN cap thickness increases from 2.5âtoâ15ânm are accompanied by clear changes in the intensity of the LO-phonon satellites. Analysis of the strength of successive phonon satellites and the associated Huang-Rhys factors indicates that the amount of localization of the excitons is increased for the thinner cap samples. Surface depletion fields are also considered
GridWeaver: A Fully-Automatic System for Microarray Image Analysis Using Fast Fourier Transforms
Experiments using microarray technology generate large amounts
of image data that are used in the analysis of genetic function.
An important stage in the analysis is the determination of
relative intensities of spots on the images generated.
This paper presents GridWeaver,
a program that reads in images from a microarray experiment,
automatically locates subgrids and spots in the images,
and then determines the spot
intensities needed in the analysis of gene function.
Automatic gridding is performed by running
Fast Fourier Transforms on pixel intensity sums.
Tests on several data sets show that the program responds
well even on images that have significant noise,
both random and systemic
CP-rays in simplicial cones
An interior point of a triangle is called CP-point if its orthogonal projection on the line containing each side lies in the relative interior of that side. In classical mathematics, interest in the concept of regularity of a triangle is mainly centered on the property of every interior point of the triangle being a CP-point. We generalize the concept of regularity using this property, and extend this work to simplicial cones in â n , and derive necessary and sufficient conditions for this property to hold in them. These conditions highlight the geometric properties of Z-matrices. We show that these concepts have important ramifications in algorithmic studies of the linear complementarity problem. We relate our results to other well known properties of square matrices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47921/1/10107_2005_Article_BF01582265.pd
The JigCell Model Builder: A Spreadsheet Interface for Creating Biochemical Reaction Network Models
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