SaaSHub helps you find the best software and product alternatives Learn more →
Top 13 Julia Ode Projects
-
DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Another up-and-coming solution is Julia's simulation ecosystem [1]. It is powered by the commercial organization behind the Julia programming language, which has received DARPA funding [2] to build out these tools. This ecosystem unifies researchers in numerical methods [3], scalable compute, and domain experts in modeling engineering systems (electrical, mechanical, etc.) I believe this is where simulation is headed.
[1] https://juliahub.com/products/juliasim
[2] https://news.ycombinator.com/item?id=26425659
[3] https://docs.sciml.ai/DiffEqDocs/stable/
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
ModelingToolkit.jl
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
JuliaSim looks interesting! From my understanding, it's 100% proprietary/commercial, but built on top of the open source https://github.com/SciML/ModelingToolkit.jl?
-
NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
-
OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
-
-
Catalyst.jl
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
-
DataDrivenDiffEq.jl
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
-
SciMLSensitivity.jl
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
-
DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
-
DiffEqGPU.jl
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
-
-
-
DiffEqDevTools.jl
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
Julia Ode discussion
Julia Ode related posts
-
2023 was the year that GPUs stood still
-
Julia as a unifying end-to-end workflow language on the Frontier exascale system
-
Modern Numerical Solving methods
-
Why Fortran is a scientific powerhouse
-
Mathematically Modelling a PRV
-
How much useful are Runge-Kutta methods of order 9 and higher within double-precision arithmetic/floating point accuracy?
-
Interpolant Coefficients for the BS5 Runge-Kutta method
-
A note from our sponsor - SaaSHub
www.saashub.com | 23 Jan 2025
Index
What are some of the best open-source Ode projects in Julia? This list will help you:
# | Project | Stars |
---|---|---|
1 | DifferentialEquations.jl | 2,894 |
2 | ModelingToolkit.jl | 1,452 |
3 | NeuralPDE.jl | 1,022 |
4 | OrdinaryDiffEq.jl | 573 |
5 | Latexify.jl | 568 |
6 | Catalyst.jl | 468 |
7 | DataDrivenDiffEq.jl | 409 |
8 | SciMLSensitivity.jl | 333 |
9 | DiffEqBase.jl | 320 |
10 | DiffEqGPU.jl | 284 |
11 | SciMLStyle | 217 |
12 | ModelingToolkitStandardLibrary.jl | 127 |
13 | DiffEqDevTools.jl | 48 |