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No representations are made about the suitability of this software for any purpose. Documents produced by doxygen are derivative works derived from the input used in their production; they are not affected by this license. It has been developed in collaboration with Finnish universities, research laboratories and industry. Elmer includes physical models of fluid dynamics, structural mechanics, electromagnetics and heat transfer.

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Elmer comprises of several different parts: The geometry, boundary conditions and physical models are defined in ElmerFront. The resulting problem definition is solved by ElmerSolver. Finally the results are visualized by ElmerPost. Additionally a utility ElmerGrid may be used for simple mesh manipulation. The different parts of Elmer software may also be used independently. The strongest of the components is ElmerSolver which includes many sophisticated features. For pre- and postprosessing the users may find also other alternatives. If this seems to be a bit of a mouthful, an easier explanation is Emacs is a text editor and more.

Some of the features of GNU Emacs include:. The EMAP codes are relatively easy to learn to use and are distributed in source code form. The EMAP codes are not intended to compete with commercial finite element modeling codes. They do not have a sophisticated mesh generator, graphical output, or unlimited technical support. Their primary strengths are ease-of-use, modest resource requirements, and accurate modeling of simple three-dimensional configurations over a wide range of frequencies.

This powerful syntax allows you to substitute analytic functions in place of numeric values sin 60 instead of 0. This feature makes it quite easy to specify a wide range of functions. The core curriculum of any first-rate undergraduate Computer Science department includes at least one course that focuses on the formal derivation and verification of algorithms 4. Yet, as the result of our search for superior methods for designing and constructing high-performance parallel linear algebra libraries, we have come to the conclusion that it is only through the systematic approach offered by formal methods that we will be able to deliver reliable, maintainable, flexible, yet highly efficient matrix libraries even in the relatively well-understood area of sequential and parallel dense linear algebra.

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In this paper we attempt to make this case. However, during the mid-nineties, the Message-Passing Interface MPI introduced to the scientific computing community a programming model, object-based programming, that possesses many of the advantages typically associated with the intelligent use of an object-oriented language 6.


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Using objects e. Our own work on the Parallel Linear Algebra Package PLAPACK borrowed from this approach in order to hide details of data distribution and data mapping in the realm of parallel linear algebra libraries 7. The primary concept also germane to this paper is that PLAPACK raises the level of abstraction at which one programs so that indexing is essentially removed from the code, allowing the routine to reflect the algorithm as it is naturally presented in a classroom setting. Since our initial work on PLAPACK , we have experimented with similar interfaces in such seemingly disparate contexts as parallel out-of-core linear algebra packages and a low-level implementation of the sequential BLAS 5.

FLAME is the latest step in the evolution of these systems. It facilitates the use of a programming style that is equally applicable to everything from out-of-core, parallel systems to single-processor systems where cache-management is of paramount concern. Over the last seven or eight years it has become apparent that what makes our task of library development more manageable is this systematic approach to deriving algorithms coupled with the abstractions we use to make our code reflect the algorithms thus produced.

Further, it is from these experiences that we can confidently state that this approach to programming greatly reduces the complexity of the resultant code and does not sacrifice high performance in order to do so. Indeed, it is exactly the formal techniques that we may have at one time dismissed as merely academic or impractical which make this possible, as FLAME illustrates. Fortran is a powerful general-purpose programming language. Fortran 77 programs may not run as expected with recent fortran compilers, because variables are not initialized to zero by default anymore.

In the case of gfortran , the old behaviour is obtained by adding -finit-local-zero to the compiling command. Graphical programs that rely on Textronix terminal -type commands to draw pictures can use xterm -t to run under Linux. Problems involving partial differential equations pde of several branches of physics such as fluid-structure interactions require interpolations of data on several meshes and their manipulation within one program.

Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.

GDB can do four main kinds of things plus other things in support of these to help you catch bugs in the act:. Those programs might be executing on the same machine as GDB native or on another machine remote.

Documentation: reference card. It lets you view and manipulate 3D objects: you use the mouse to rotate, translate, zoom in and out, etc. It can be used as a standalone viewer for static objects or as a display engine for other programs which produce dynamically changing geometry. It can display objects described in a variety of file formats. It comes with a wide selection of example objects, and you can create your own objects too.

The main feature of GetDP is the closeness between the input data defining discrete problems written by the user in ASCII data files and the symbolic mathematical expressions of these problems. Which problems can GetDP actually solve? The goal is to provide a library allowing the computation of any elementary matrix even for mixed finite element methods on the largest class of methods and elements, and for arbitrary dimension i.

It offers a complete separation between integration methods exact or approximated , geometric transformations linear or not and finite element methods of arbitrary degrees.

It can really relieve a more integrated finite element code of technical difficulties of elementary computations. Examples of available finite element method are : Pk on simplices in arbitrary degrees and dimensions, Qk on parallelepipeds, P1, P2 with bubble functions, Hermite elements, elements with hierarchic basis for multigrid methods for instance , discontinuous Pk or Qk, XFem, …. The addition of a new finite element method is straightforward. Its description on the reference element must be provided in most of the cases, this is the description of the basis functions, and nothing more.

Extensions are provided for Hermite elements, piecewise polynomial, non-polynomial and vectorial elements, XFem. The library also includes the usual tools for finite elements such as assembly procedures for classical PDEs, interpolation methods, computation of norms, mesh operations, boundary conditions, post-processing tools such as extraction of slices from a mesh …. Examples are provided see the screenshot section. A particular method allows to interpolate a finite element method on an arbitrary mesh allowing any assembly procedure to work with two different meshes.

This is usefull for some mixed finite element methods and for mortar methods with non-matching meshes. The model is general in the sense that it can be applied to various systems, scales and specifications. The model includes for example flooding and drying of tidal flats, flexible vertical and horizontal coordinate systems, different turbulence models integrated from GOTM , and is a Public Domain model published under GNU Public Licence.

Its primal design goal is to provide a simple meshing tool for academic test cases with parametric input and up to date visualization capabilities. One of its strengths is the ability to respect a characteristic length field for the generation of adapted meshes on lines, surfaces and volumes, and to mix these meshes with simple structured grids. Make gets its knowledge of how to build your program from a file called the makefile, which lists each of the non-source files and how to compute it from other files. When you write a program, you should write a makefile for it, so that it is possible to use Make to build and install the program.

The library provides a wide range of mathematical routines such as random number generators, special functions and least-squares fitting. There are over functions in total. Unlike the licenses of proprietary numerical libraries the license of GSL does not restrict scientific cooperation. It allows you to share your programs freely with others. It is an Open Source Free Software Library intended to provide a set of useful functions to deal with 3D surfaces meshed with interconnected triangles. Careful attention is paid to performance related issues as the initial goal of GTS is to provide a simple and efficient library to scientists dealing with 3D computational surface meshes.

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It is a one-dimensional water column model for the most important hydrodynamic and thermodynamic processes related to vertical mixing in natural waters. In addition, it has been designed such that it can easily be coupled to 3-D circulation models, and used as a module for the computation of vertical turbulent mixing.

The core of the model computes solutions for the one-dimensional versions of the transport equations of momentum, salt and heat. The key component in solving these equations is the model for the turbulent fluxes of these quantities. The strength of GOTM is the vast number of well-tested turbulence models that have been implemented in the code. These models span the range from simple prescribed expressions for the turbulent diffusivities up to complex Reynolds-stress models with several differential transport equations to solve.

Even though, evidently, not all turbulence models published in oceanography could be implemented, at least one member of every relevant model family can be found in GOTM: empirical models, energy models, two-equation models, Explicit Algebraic Stress Models EASM , and K-profile parameterisations KPP.

The goal of the GRUMMP project is to develop automatic mesh generation software for unstructured meshes with mixed element types. The software should produce high-quality meshes that meet user-defined mesh density requirements, using elements appropriate for the geometry and physics of a particular problem. Automatic mesh generation for complex two and three dimensional domains is a topic of intensive research.

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It is imperative that automatic mesh generation tools be capable of generating quality finite element and finite volume meshes. There must be a balance between resolution of the boundary and surface features and complexity of the problem. In addition, for problems with isotropic physics, element aspect ratio must be small to minimize linear system condition number and interpolation error.

On the other hand, problems with anisotropic physics for example, a shear layer in viscous fluid flow require highly anisotropic elements for efficient solution. A further level of complication is that for some physical problems and applications, quadrilateral 2D or hexahedral 3D elements are preferred, even though filling space with high quality elements is easier using triangular 2D or tetrahedral 3D elements.

A general-purpose automatic mesh generator should address all of these issues without excessive user intervention. We envision a system in which common types of physical problems have predefined mesh sizing and element aspect ratio functions, allowing easy generation of meshes for these applications areas.

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