JuliaSim - Julia Computing

JuliaSim is a next generation cloud-based simulation platform, combining the latest techniques in SciML 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.

Bringing Julia to Industrial Scale Modeling and Simulation

JuliaSim allows you to directly import models from its Model Store into your Julia environment, making it easy to build large complex simulations. Pre-trained machine learning models leveraging SciML are seamlessly integrated into the engineer's workflow, saving both model development and simulation time. Design your physical product right and reduce iterations by creating high-fidelity designs, automatically transforming them into accelerated versions, and searching through vast parameter spaces. Consult the documentation for more details.

Accelerate with Surrogates

Generate fast approximate models using the latest techniques from scientific machine learning and model order reduction.

Integrate with Uncertainty Quantification and Noise

Use advanced techniques like Polynomial Chaos and Koopman Operator approaches to create designs robust to uncertainty and stochasticity.

Parameter Estimation and Optimal Control

Integrate with Julia’s differentiable programming for high-performance stable adjoints to accelerate parameter estimation and optimizing controls.

Model Discovery

Combine models with tools like DiffEqFlux and NeuralPDE to discover missing physics and generate digital twins.

Combine with Pre-Built Models and Digital Twins

Grab complete models from the JuliaSim Model Store and compose the pieces to accelerate the design process.

Specialized Numerical Environments

Use the latest numerical tools, like discontinuity-aware differential equation solvers, high-performance steady state solvers, and domain-specific environments.