BytedTsinghua-SIA/CUDA-Agent

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1256 stars · 121 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CUDA-Agent is a large-scale agentic reinforcement learning system from ByteDance Seed and Tsinghua that trains LLMs to generate high-performance CUDA kernels, achieving state-of-the-art results on KernelBench and outperforming torch.compile. It releases the CUDA-Agent-Ops-6K training dataset, an expert-designed SKILL.md agent environment, and a standardized workspace for the implement-compile-verify-profile loop.

Use cases

• generate optimized CUDA kernels with an LLM agent
• train a model with agentic RL for GPU kernel code generation
• benchmark CUDA kernel generation against torch.compile on KernelBench
• synthesize training data for CUDA operator fusion tasks
• set up an agent workspace to compile, verify, and profile custom CUDA kernels
• speed up PyTorch models with RL-generated CUDA extensions

When to choose

• you need state-of-the-art CUDA kernel generation that beats torch.compile
• you want to reproduce or extend agentic RL training for code optimization
• you need a curated dataset of executable, deterministic CUDA operator tasks
• you want a ready-made environment for the kernel implement-verify-profile loop

When to avoid

• you need a production inference library rather than a research training system
• you have no NVIDIA GPU or CUDA development toolchain
• you want a no-code tool for accelerating PyTorch models
• you require a permissively licensed dependency - the repo has no license file

Facets

framework · maturity active

machine-learning llm-training agent-framework gpu-computing benchmarking data-generation machine-learning gpu-computing artificial-intelligence reinforcement-learning large-language-models deep-learning performance python cuda-kernels reinforcement-learning agentic-rl kernel-generation kernelbench pytorch code-generation llm-agents training-dataset gpu-optimization ai-agents gpu linux docker

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For agents

markdown · JSON · MCP: product_card(name="BytedTsinghua-SIA/CUDA-Agent")