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A 2013 article and interview with the main developer published in Libre Graphics World has praised SolveSpace for its small executable file size, advanced constraints solver, and output formats. [23] However, it was also criticized for some drawbacks it had at the time, such as limited support for NURBS (i.e. Boolean operations) and a lack of ...
Linux, Windows: Agros2D: Multiplatform open source application for the solution of physical problems based on the Hermes library: University of West Bohemia: 3.2: 2014-03-03: GNU GPL: Free: Linux, Windows: CalculiX: It is an Open Source FEA project. The solver uses a partially compatible ABAQUS file format. The pre/post-processor generates ...
Lis (Library of Iterative Solvers for linear systems; pronounced lis]) is a scalable parallel software library to solve discretized linear equations and eigenvalue problems that mainly arise from the numerical solution of partial differential equations using iterative methods.
The SciPy scientific library, for instance, uses HiGHS as its LP solver [13] from release 1.6.0 [14] and the HiGHS MIP solver for discrete optimization from release 1.9.0. [15] As well as offering an interface to HiGHS, the JuMP modelling language for Julia [ 16 ] also describes the specific use of HiGHS in its user documentation. [ 17 ]
The software runs on Unix and Windows platforms and can be compiled on a large variety of compilers, using the CMake building tool. The solver can also be used in a multi-host parallel mode on platforms that support MPI. Elmer's parallelisation capability is one of the strongest sides of this solver.
There is a friendly CalculiX Launcher [7] with CCX wizard for both Windows and Linux. [8] Also possible is the Installation in Windows 10 Fall Creator (1709) with the new Linux Subsystem WSL. [9] A Python library, pycalculix, [10] was written to automate the creation of CalculiX models in the Python programming language. The library provides ...
GEKKO works on all platforms and with Python 2.7 and 3+. By default, the problem is sent to a public server where the solution is computed and returned to Python. There are Windows, MacOS, Linux, and ARM (Raspberry Pi) processor options to solve without an Internet connection.
Both binaries and source code are available for SageMath from the download page. If SageMath is built from source code, many of the included libraries such as OpenBLAS, FLINT, GAP (computer algebra system), and NTL will be tuned and optimized for that computer, taking into account the number of processors, the size of their caches, whether there is hardware support for SSE instructions, etc.