Numerical Linear Algebra Packages

IterativeSolvers.jl358Iterative algorithms for solving linear systems, eigensystems, and singular value problems

Elemental.jl69Julia interface to the Elemental linear algebra library.

BSplines.jl21A Julia package for working with Bsplines

TaylorModels.jl58Rigorous function approximation using Taylor models in Julia

TensorToolbox.jl55Julia package for tensors as multidimensional arrays, with functionalty within Tucker format, Kruskal (CP) format, Hierarchical Tucker format and Tensor Train format.

JuliaFEM.jl226The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

ArnoldiMethod.jl72Implicitly Restarted Arnoldi Method, natively in Julia

RandomizedPreconditioners.jl33

Cuba.jl72Library for multidimensional numerical integration with four independent algorithms: Vegas, Suave, Divonne, and Cuhre.

ToeplitzMatrices.jl59Fast matrix multiplication and division for Toeplitz matrices in Julia

Sparspak.jl33Direct solution of large sparse systems of linear algebraic equations in pure Julia

TetGen.jl33Julia's TetGen wrapper

SpecialMatrices.jl38Julia package for working with special matrix types.

NumericExtensions.jl56Julia extensions to provide high performance computational support

NonlinearEigenproblems.jl89Nonlinear eigenvalue problems in Julia: Iterative methods and benchmarks

RungeKuttaFehlberg.jl0A Julia implementation of the RKF45 method for time integration

MiniBall.jl4Julia package for a smallest enclosing sphere for points in arbitrary dimensions

GenericSVD.jl41Singular Value Decomposition for generic number types

KrylovMethods.jl44Simple and fast Julia implementation of Krylov subspace methods for linear systems.

FEMBasis.jl11FEMBasis contains interpolation routines for finite element function spaces. Given ansatz and coordinates of domain, shape functions are calculated symbolically in a very general way to get efficient code. Shape functions can also be given directly and in that case partial derivatives are calculated automatically.

IncrementalSVD.jl31Simon Funk's approach to collaborative filtering using the singular value decomposition, implemented in Julia.

NumericFuns.jl13Math functions and functors for numerical computations

NumericFunctors.jl13Math functions and functors for numerical computations

NumericalShadow.jl2Numerical shadow library for Julia language

RK4.jl0

IterativeLinearSolvers.jl3Translations of "Templates for the Solution of Linear Systems: Building, Blocks for Iterative Methods" to Julia

ParallelLinalg.jl1Distributed Dense Linear Algebra for Julia

Accelereval.jl1A Julia framework for accelerated recompiled evaluation.
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