Search Results for "solver"
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Showing 28 open source projects for "solver"
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SCIP.jl
Julia interface to SCIP solver
SCIP.jl is a Julia interface to the SCIP solver. This wrapper is maintained by the SCIP project with the help of the JuMP community. -
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HiGHS.jl
Julia wrapper for the HiGHS solver
HiGHS.jl is a wrapper for the HiGHS solver. -
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VoronoiFVM.jl
Solution of nonlinear multiphysics partial differential equations
Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters. -
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Tulip.jl
Interior-point solver in pure Julia
Tulip is an open-source interior-point solver for linear optimization, written in pure Julia. It implements the homogeneous primal-dual interior-point algorithm with multiple centrality corrections and therefore handles unbounded and infeasible problems. Tulip’s main feature is that its algorithmic framework is disentangled from linear algebra implementations. This allows to seamless integration of specialized routines for structured problems. -
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over the... -
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NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
...The package includes its own high-performance nonlinear solvers which include the ability to swap out to fast direct and iterative linear solvers, along with the ability to use sparse automatic differentiation for Jacobian construction and Jacobian-vector products. NonlinearSolve.jl interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. -
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Sundials.jl
Julia interface to Sundials, including a nonlinear solver
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. -
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Coluna.jl
Branch-and-Price-and-Cut in Julia
Coluna is a branch-and-price-and-cut framework written in Julia. You write an original MIP that models your problem using the JuMP modeling language and our specific extension BlockDecomposition offers a syntax to specify the problem decomposition. Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm. -
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DiffOpt.jl
Differentiating convex optimization programs w.r.t. program parameters
DiffOpt.jl is a package for differentiating convex optimization programs (JuMP.jl or MathOptInterface.jl models) with respect to program parameters. Note that this package does not contain any solver. This package has two major backends, available via the reverse_differentiate! and forward_differentiate! methods, to differentiate models (quadratic or conic) with optimal solutions. Differentiable optimization is a promising field of convex optimization and has many potential applications in game theory, control theory and machine learning. ... -
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EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing... -
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BlockArrays.jl
BlockArrays for Julia
...This means that BlockArray supports fast noncopying extraction and insertion of blocks while PseudoBlockArray supports fast access to the full matrix to use in for example a linear solver. -
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ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
...Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array programming implementation; in absolute terms, it reached 70% of the theoretical upper performance bound of the used Nvidia P100 GPU, as defined by the effective throughput metric, T_eff. ParallelStencil relies on the native kernel programming capabilities of CUDA.jl and AMDGPU.jl and on Base.Threads for high-performance computations on GPUs and CPUs, respectively. ... -
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LinearSolve.jl
High-Performance Unified Interface for Linear Solvers in Julia
LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems, with options for large-scale systems. ... -
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SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem. -
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ProxSDP.jl
Semidefinite programming optimization solver
ProxSDP is an open-source semidefinite programming (SDP) solver based on the paper "Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting". The main advantage of ProxSDP over other state-of-the-art solvers is the ability to exploit the low-rank structure inherent to several SDP problems. -
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ConstraintSolver.jl
ConstraintSolver in Julia
This package aims to be a constraint solver completely written in Julia. The concepts are more or less fully described on my blog OpenSourc.es. There is of course also the general user manual here which explains how to solve your model. -
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Nova
Astronomical Image Solver with Telescope Pointing
Nova is a simple astronomical image solver. It can currently open FITS files and identify some objects against star catalog objects. -
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Happy Cube Solver
Design and Display Happy Cube solutions
The Happy Cube Solver is an interactive interface for designing and building cubes and other designs from the Happy Cube 3D puzzles. It integrates a graphic engine for creating and viewing designs and a simple engine for solving them. Online version: http://shooshx.github.io/happysolver/emscripten/index.html Maintainance of this project moved to: https://github.com/shooshx/happysolver This program is indented to support you while playing live with the Happy Cube©® Puzzles. ... -
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Impact is an explicit Finite Element Program Suite which simulates dynamic impact events. It has a range of elements, contact handling and different material laws. Models can be created, solved and analyzed with the included pre- and postprocessor. Impact is based on an Explicit Time stepping algorithm. These kind of codes are used to simulate dynamic phenomena such as car crashes and similar, usually involving large deformations.
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Runge
Runge is an Interactive Solver for Systems of Differential Equations
Runge is an Interactive Solver for Systems of Ordinary Differential Equations. It solves initial value problem (aka Cauchy problem). Few advantages Runge provides: It's fast. It utilizes BLAS and LAPACK libraries optimized for modern multi-core processors. It's interactive. It allows you to start a solution by mouse click on a plane. It's precise. -
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CAPLET
GDS visualization and parallelized capacitance extraction
Project CAPLET is a capacitance extraction toolkit that extract capacitance at field-solver accuracy. CAPLET can directly handle GDS2 layout files into capacitance matrices in both GUI and command line interfaces. The internal extraction algorithm is specialized for VLSI interconnect structures but not exclusively, as long as the structure is of Manhattan geometry and embedded in a uniform dielectric material. -
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This is a client/server/CORBA software aiming at solving partial differential equations.The server provides the solver while the client provides the input data and the handling of the output using a graphic library, vtk.
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An object-oriented partial differential equation (PDE) solver, written in Python, based on a standard finite volume approach and includes interface tracking algorithms. *WARNING* The project is no longer using Sourceforge to maintain its repository.
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A Fast MAC based 3D Free surface fuid solver. Capable also of simulating viscoelastic fluids.Includes also wave equation solver for simulating shallow water phenomena.
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An automatic 2D Delaunay mesh generator and solver for Finite Element Analysis. Can solve 2D field problems (Poisson and Helmholtz Equations). Can use LAPACK/ARPACK solvers producing OpenGL/Postscript output. Uses C/GTK/GTKGLExt/MFC. Runs on Win32/Unix.
