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MFEM is a free, lightweight, scalable C++ library for finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretizations, and emphasis on usability, generality, and high-performance computing efficiency.
Finite element method (FEM) analysis software that runs on Linux. Pages in category "Finite element software for Linux" The following 34 pages are in this category, out of 34 total.
Pages in category "Free software programmed in Python" The following 200 pages are in this category, out of approximately 313 total. This list may not reflect recent changes .
Linux is a Unix-like computer operating system assembled under the model of free and open-source software development and distribution. Most Linux distributions , as collections of software based around the Linux kernel and often around a package management system , provide complete LAMP setups through their packages.
If A and B are sets and every element of A is also an element of B, then: . A is a subset of B, denoted by , or equivalently,; B is a superset of A, denoted by .; If A is a subset of B, but A is not equal to B (i.e. there exists at least one element of B which is not an element of A), then:
Version 2.0 introduced an implementation of the primal-dual interior point method. Version 2.2 added branch and bound solving of mixed integer problems. Version 2.4 added a first implementation of the GLPK/L modeling language. Version 4.0 replaced GLPK/L by the GNU MathProg modeling language, which is a subset of the AMPL modeling language.
The multiple subset sum problem is an optimization problem in computer science and operations research.It is a generalization of the subset sum problem.The input to the problem is a multiset of n integers and a positive integer m representing the number of subsets.
It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.