Slang is a modern shader language and compiler that extends traditional graphics programming with powerful machine learning capabilities. Building on its foundation as a high-performance shading language for real-time graphics, Slang integrates features like automatic differentiation and interoperability with Python-based ML training frameworks like PyTorch, allowing you to incorporate custom GPU operations directly into neural network training workflows.
Slang provides built-in automatic differentiation capabilities that can transform complex shader code into differentiable functions. This allows you to:
Whether you're implementing gradient-based optimization, neural rendering, or differentiable simulation, Slang's autodiff capabilities provide the foundation you need.
Learn more about Automatic DifferentiationSlangPy enables direct integration of Slang code into Python-based ML training frameworks like PyTorch, bridging the gap between high-performance GPU programming and machine learning workflows. With SlangPy, you can:
SlangPy makes it easy to extend your Python-based machine learning workflows with custom GPU code when you need performance and flexibility beyond what standard frameworks provide.
Explore SlangPySlang provides a complete workflow for machine-learning-enchanced graphics development that leverages its shader language foundation:
Write high-performance shader code in Slang, leveraging familiar HLSL-like syntax and advanced shader language features like generics and interfaces.
Use automatic differentiation to transform your shaders into differentiable code for training neural networks or optimization algorithms.
Connect your Slang code to Python-based ML training frameworks like PyTorch, enabling custom GPU operations within training loops.
Compile your shaders to multiple backend targets (CUDA, HLSL, SPIR-V, etc.) for cross-platform deployment in both graphics and ML contexts.
Take advantage of Slang's shader module system and compilation model to minimize compile times and maximize runtime performance.
Use comprehensive shader tooling support for faster development cycles and easier debugging in both graphics and ML contexts.
Combining Slang's shader language capabilities with machine learning opens up unique opportunities:
Implement neural rendering techniques like NeRF, neural radiance caching, and learned material models directly in your rendering pipeline using Slang shaders.
Create high-performance custom operators as Slang shaders for machine learning frameworks when standard operations don't meet your needs.
Build differentiable physics, cloth, fluid, and particle simulation shaders that can be optimized through gradient-based methods.
Prototype and experiment with novel neural graphics algorithms using Slang's flexible shader language designed specifically for graphics programmers.
Integrate machine learning components into existing graphics shader pipelines without sacrificing performance or portability, maintaining a single shader language across your codebase.
Implement efficient sparse data structures and algorithms that aren't well-supported by tensor-based ML frameworks.
Ready to explore machine learning with Slang? Check out these resources to get started: