CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

Weinan Dai, Hanlin Wu, Qiying Yu, Huan-ang Gao, Jiahao Li et al.|February 27, 2026arXiv

Key Takeaway

Reinforcement learning can teach AI models to write genuinely optimized GPU code, not just syntactically correct code—a task that previously requ...

Summary

This paper trains an AI agent to write optimized GPU code (CUDA kernels) using reinforcement learning. The system learns from trial-and-error feedback about code performance, achieving faster execution than existing tools like PyTorch's compiler and outperforming top commercial AI models on benchmark tests.

agents training applications

Key Terms

cuda-kernels reinforcement-learning reward-signal kernel-optimization