XLB
A differentiable, massively parallel Lattice Boltzmann library in Python for physics-based machine learning and fluid dynamics simulations.
What is XLB?
XLB is a differentiable, massively parallel Lattice Boltzmann Method library in Python for simulating fluid dynamics. It solves complex flow problems efficiently while providing differentiable kernels that enable seamless integration with machine learning frameworks for physics-based AI applications.
Researchers and engineers in computational fluid dynamics, physics-based machine learning, and scientific computing who need scalable, differentiable simulations for optimization and AI-driven design.
Developers choose XLB for its unique combination of full differentiability, massive parallel scalability across multiple hardware backends, and user-friendly Python interface that bridges traditional CFD with modern ML workflows.
Overview
XLB: Accelerated Lattice Boltzmann (XLB) for Physics-based ML
Use Cases
Best For
- Physics-informed neural networks requiring differentiable fluid simulations
- Large-scale computational fluid dynamics research on multi-GPU clusters
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