- ComponentArrays.jl VS DiffEqBase.jl
- ComponentArrays.jl VS JuMP.jl
- ComponentArrays.jl VS RayTracer.jl
- ComponentArrays.jl VS ModelingToolkit.jl
- ComponentArrays.jl VS ControlSystems.jl
- ComponentArrays.jl VS GeoStats.jl
- ComponentArrays.jl VS FunctionalCollections.jl
- ComponentArrays.jl VS DSGE.jl
- ComponentArrays.jl VS julia
- ComponentArrays.jl VS DifferentialEquations.jl
ComponentArrays.jl Alternatives
Similar projects and alternatives to ComponentArrays.jl
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DiffEqBase.jl
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DSGE.jl
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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.
ComponentArrays.jl reviews and mentions
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Recursion absolutely necessary for distributed computing?
But for these to be as fast as say an Array when being used as the object in a differential equation solve or as the underlying construct of a nonlinear optimization, you would need the compiler to elide the struct construction which it doesn't always do. This is why the tools evolved to be around things like https://github.com/jonniedie/ComponentArrays.jl instead, where it's an Array-backed object with a higher level. Such immutable objects are used in these array-like contexts when the problems are small enough (FieldVectors or SLVector LabelledArrays.jl in DiffEq), and such applications work well in Haskell as well, but I haven't seen a compiler do well with say a 1,000 ODE model written in this style. And it's not quite an extreme case if it's what people are doing daily.
Stats
jonniedie/ComponentArrays.jl is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of ComponentArrays.jl is Julia.