Numerical Linear Algebra Packages

NumericalShadow.jl3Numerical shadow library for Julia language

ParallelLinalg.jl1Distributed Dense Linear Algebra for Julia

NumericExtensions.jl57Julia extensions to provide high performance computational support

ToeplitzMatrices.jl66Fast matrix multiplication and division for Toeplitz matrices in Julia

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

IterativeSolvers.jl401Iterative algorithms for solving linear systems, eigensystems, and singular value problems

KrylovMethods.jl45Simple and fast Julia implementation of Krylov subspace methods for linear systems.

Accelereval.jl1A Julia framework for accelerated recompiled evaluation.

RK4.jl0

NumericFunctors.jl13Math functions and functors for numerical computations

NumericFuns.jl13Math functions and functors for numerical computations

SpecialMatrices.jl39Julia package for working with special matrix types.

TetGen.jl42Julia's TetGen wrapper

Elemental.jl78Julia interface to the Elemental linear algebra library.

JuliaFEM.jl250The 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.

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

GenericSVD.jl41Singular Value Decomposition for generic number types

Cuba.jl75Library for multidimensional numerical integration with four independent algorithms: Vegas, Suave, Divonne, and Cuhre.

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

TensorToolbox.jl64Julia package for tensors as multidimensional arrays, with functionalty within Tucker format, Kruskal (CP) format, Hierarchical Tucker format and Tensor Train format.

FEMBasis.jl14FEMBasis 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.

TaylorModels.jl63Rigorous function approximation using Taylor models in Julia

ArnoldiMethod.jl96The Arnoldi Method with KrylovSchur restart, natively in Julia.

NonlinearEigenproblems.jl92Nonlinear eigenvalue problems in Julia: Iterative methods and benchmarks

IncrementalSVD.jl8Incrementally compute an approximate truncated singular value decomposition

BSplines.jl26A Julia package for working with Bsplines

RandomizedPreconditioners.jl44

Sparspak.jl37Direct solution of large sparse systems of linear algebraic equations in pure Julia
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