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deepmind.google·6d ago
AI Engineering
Lobsters·Sep 9·5 min read
Introducing CUDA Rust: Two Tracks for Writing GPU Kernels
TL;DR
NVIDIA has introduced CUDA Rust, enabling developers to write GPU kernels directly in Rust, enhancing performance and safety. This initiative aims to close the gap in native GPU programming as Rust gains traction in systems-level AI development.
✦ Why It Matters
Start exploring CUDA Rust today to leverage its safety features in GPU kernel development.
Key Takeaways
- Experiment with CUDA Rust for safer GPU kernel development.
- Use the Tile model for easier data handling in GPU programming.
- Check compatibility with compute capability 8.0 or later GPUs.
- Engage with the Rust community to shape future GPU programming tools.
How It Works
CUDA Rust allows developers to write GPU kernels in Rust, compiling them directly to PTX. It offers two programming models: SIMT, which operates like traditional CUDA, and Tile, which abstracts data handling to simplify kernel development.
The Tile model enables the compiler to manage architecture-specific optimizations, reducing the burden on developers.