- DiffEqOperators.jl VS BoundaryValueDiffEq.jl
- DiffEqOperators.jl VS Gridap.jl
- DiffEqOperators.jl VS ApproxFun.jl
- DiffEqOperators.jl VS FourierFlows.jl
- DiffEqOperators.jl VS SciMLTutorials.jl
- DiffEqOperators.jl VS oxide-enzyme
- DiffEqOperators.jl VS julia
- DiffEqOperators.jl VS DifferentialEquations.jl
- DiffEqOperators.jl VS mujoco
- DiffEqOperators.jl VS Infiltrator.jl
DiffEqOperators.jl Alternatives
Similar projects and alternatives to DiffEqOperators.jl
-
BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
-
Gridap.jl
Grid-based approximation of partial differential equations in Julia
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
FourierFlows.jl
Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains
-
oxide-enzyme
Discontinued Enzyme integration into Rust. Experimental, do not use.
-
SciMLTutorials.jl
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
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.
-
mujoco
Multi-Joint dynamics with Contact. A general purpose physics simulator.
-
-
-
-
-
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
-
-
SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
-
OMEinsum.jl
One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
-
jlpkg
A command line interface (CLI) for Pkg, Julia's package manager.
-
Catwalk.jl
An adaptive optimizer for speeding up dynamic dispatch in Julia
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better DiffEqOperators.jl alternative or higher similarity.
DiffEqOperators.jl reviews and mentions
Posts with mentions or reviews of DiffEqOperators.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-30.
-
Julia 1.7 has been released
>I hope those benchmarks are coming in hot
M1 is extremely good for PDEs because of its large cache lines.
https://github.com/SciML/DiffEqOperators.jl/issues/407#issue...
The JuliaSIMD tools which are internally used for BLAS instead of OpenBLAS and MKL (because they tend to outperform standard BLAS's for the operations we use https://github.com/YingboMa/RecursiveFactorization.jl/pull/2...) also generate good code for M1, so that was giving us some powerful use cases right off the bat even before the heroics allowed C/Fortran compilers to fully work on M1.
-
What's Bad about Julia?
I like that they are colored now, but really what needs to be added is type parameter collapasing. In most cases, you want to see `::Dual{...}`, i.e. "it's a dual number", not `::Dual{typeof(ODESolution{sfjeoisjfsfsjslikj},sfsef,sefs}` (these can literally get to 3000 characters long). As an example of this, see the stacktraces in something like https://github.com/SciML/DiffEqOperators.jl/issues/419 . The thing is that it gives back more type information than the strictest dispatch: no function is dispatching off of that first 3000 character type parameter, so you know that printing that chunk of information is actually not informative to any method decisions. Automated type abbreviations could take that heuristic and chop out a lot of the cruft.
Stats
Basic DiffEqOperators.jl repo stats
3
281
4.6
10 months ago
SciML/DiffEqOperators.jl is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of DiffEqOperators.jl is Julia.
Popular Comparisons
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com