This talk introduces cadCAD.jl, a high performance open source Julia library for modeling and simulating dynamical systems with generic attributes. Our goal with this talk is to show the main ideas behind the library, how it promotes open science, how we used Julia to achieve higher performance in comparison to it's Python implementation, and how it would fit in a data science workflow, by running an example simulation.
This talk introduces cadCAD.jl, a high performance open source Julia library for modeling and simulating dynamical systems with generic attributes. Instead of evolving numbers over time, system engineers and data scientists can now evolve any kind of data structure in their dynamical systems simulations. With cadCAD.jl, models of these systems can yield:
Our goal with this talk is to show the main ideas behind the library, how it promotes open science, how we used Julia to achieve higher performance in comparison to it's Python implementation, and how it would fit in a data science workflow, by running an example simulation.