Scientific computing ecosystem

Questions

• What libraries are available for scientific computing in Julia?

Instructor note

• 10 min teaching

• 0 min exercises

Ecosystem of scientific computing packages

Julia has a rich and rapidly expanding ecosystem of packages for scientific computing in many scientific domains. In many cases developers of individual packages join forces to create mutually compatible and supporting packages organized under a common GitHub organization. The following list can be of some help in navigating the ecosystem.

Mathematics

• JuliaDiff – Differentiation tools

• JuliaGeometry – Computational Geometry

• JuliaGraphs – Graph Theory and Implementation

• JuliaIntervals - Rigorous numerics with interval arithmetic & applications

• JuliaMath – Mathematics made easy in Julia

• JuliaOpt – Optimization

• JuliaPolyhedra – Polyhedral computation

• JuliaSparse – Sparse matrix solvers

• JuMP-dev - Modeling language for mathematical optimization

Scientific domains

• BioJulia – Biology

• EcoJulia – Ecology

• JuliaAstro – Astronomy

• JuliaDSP – Digital signal processing

• JuliaQuant – Finance

• JuliaQuantum – Julia libraries for quantum science and technology

• QuantumBFS – Extensible, Efficient Quantum Algorithm Design for Humans

• JuliaPhysics – Physics

• JuliaDynamics - Dynamical systems, nonlinear dynamics and chaos.

Data sciences

• SciML – Scientific machine learning

• FluxML - Machine learning stack

• JuliaML – Machine Learning

• JuliaStats – Statistics

• JuliaImages – Image Processing

• JuliaText – Natural Language Processing (NLP), Computational Linguistics and (textual) Information Retrieval

• JuliaDatabases – Various database drivers for Julia

• JuliaData – Data manipulation, storage, and I/O in Julia

Scientific computing libraries

• Which, if any, libraries and packages do you use for scientific computing?

• Do you see something interesting in the list above?