Numerical Computing in Julia

by Martin D. Maas, Ph.D

This is an expanding series of tutorials of numerical computing in Julia.

Interpolation, Integration, Least Squares, and more...


This tutorial series is an introduction on programming and understanding numerical methods in Julia. We will cover several topics.

Basic familiarity with Julia and VSCode is assumed. If you are a beginner, you can check out my series on The Julia Programming Language: an Effective Tutorial

I’ve also moved my chapter on the FFT to a separate, dedicated tutorial: Using the Fast Fourier Transform.

Best Julia Packages for Numerical Computing

Here is an opinionated and incomplete list of some of the best packages for numerical computing in Julia.

Problem typeJulia packages
Linear system / least squaresLinearSolve
Sparse matrixSparseArrays
InterpolationDataInterpolations, ApproxFun
Polynomial manipulationsPolynomials
Finite differencesFiniteDifferences, FiniteDiff
IntegrationQuadgk, HCubature
Ordinary Differential EquationsDifferentialEquations
Finite Element MethodGridap
Hyperbolic PDETrixi
Automatic DifferentiationForwardDiff, Enzyme
Fast Fourier TransformFFTW

I’ll be reviewing most of them in the next chapters, and providing examples!

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