The JuliaSim software is available for preview only. Please contact us for access, by emailing [email protected], if you are interested in evaluating JuliaSim.
JuliaSim is a next generation cloud-based simulation platform, combining the latest techniques in Scientific Machine Learning with equation-based digital twin modeling and simulation. Our modern ML-based techniques accelerate simulation by up to 500x, changing the paradigm of what is possible with computational design. The premise of the software is to facilitate the design and accelerate challenging real-life models of considerable complexity.
JuliaSim allows the user to import models directly from the Model Store (more information below) into the Julia environment, making it easy to build large complex simulations. The user-friendly GUI facilitates the process and makes simulation more accessible to a wider audience.
JuliaSim produces surrogates of blackbox (and regular) dynamical systems using Continuous Time Echo State Networks (CTESNs). This novel technique allows, amongst other features, for implicit training in parameter space to stabilize the ill-conditioning present in stiff systems.
In our series of tutorials, we focus on JuliaSim's seamless integration with related packages. This feature allows the user to harness the power of multiple packages in a structured manner.
Acceleration with surrogates
Integration with uncertainty quantification and noise
Parameter estimation and optimal control
Model discovery
Combination with pre-built models and digital twins
Specialized numerical environments
Model exchange
Intuitive GUI