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On the recordRead 8 Oct 202627 facts
Kinetic.jl
On the record
- Applications
- It supports particle transport and advection-diffusion-type equations involving particles such as molecules, photons, plasmas, and neutrons.xiaotianbai.com · read 8 Oct 2026
- Assessment tools
- Nogithub.com · read 24 Sep 2026
- Authoring tools
- Nogithub.com · read 24 Sep 2026
- Compute
- The documentation says simultaneous one to three dimensional simulations can run on CPUs and GPUs.xiaotianbai.com · read 8 Oct 2026
- Delivery mode
- desktopgithub.com · read 24 Sep 2026
- Design
- The project describes its modular design as supporting educational use in kinetic theory and scientific research through APIs at different levels.xiaotianbai.com · read 8 Oct 2026
- Distributed computing
- The distributed computing documentation uses Julia's Distributed module and describes its @distributed macro as providing MPI-type parallelization.xiaotianbai.com · read 7 Oct 2026
- Education and research
- The interface is intended for educational use in kinetic theory and scientific research, with multiple API levels designed to cooperate with Julia ecosystem packages.xiaotianbai.com · read 7 Oct 2026
- Fortran backend
- KitFort is an optional Fortran backend that can be manually installed when execution efficiency is the priority; it is not a default Kinetic submodule.xiaotianbai.com · read 8 Oct 2026
- Julia ecosystem
- The documentation describes Kinetic as a 100% Julia stack designed to integrate with existing Julia packages and avoid a two-language workflow.xiaotianbai.com · read 8 Oct 2026
- Lesson library
- Nogithub.com · read 24 Sep 2026
- Machine learning
- KitML is a scientific machine learning toolbox intended to fuse mechanical and neural models, including a neural network enhanced Boltzmann equation.xiaotianbai.com · read 8 Oct 2026
- ML integrations
- KitML documentation says its training interfaces are consistent with the Flux.jl and DiffEqFlux.jl ecosystems and that its universal Boltzmann equation works with DifferentialEquations.jl solvers.xiaotianbai.com · read 8 Oct 2026
- ODE integration
- The universal Boltzmann equation functions are documented as working with modern ODE solvers in DifferentialEquations.jl.xiaotianbai.com · read 7 Oct 2026
- Offline access
- Yesgithub.com · read 24 Sep 2026
- Parallel computing
- The distributed computing guide uses Julia's Distributed module and describes MPI-type parallelization across workers.xiaotianbai.com · read 8 Oct 2026
- Product
- Kinetic.jl is a computational fluid dynamics toolbox written in Julia that combines mechanical and neural network models in a differentiable programming framework.xiaotianbai.com · read 8 Oct 2026
- Purpose
- Kinetic is a computational fluid dynamics toolbox written in Julia that combines mechanical and neural network models in a unified framework.xiaotianbai.com · read 7 Oct 2026
