Curated, minimal artifacts showcasing KernelAgent/Fuser outputs across L1/L2/L3.
Source repo: https://github.com/meta-pytorch/KernelAgent Blog post: https://pytorch.org/blog/kernelfalcon-autonomous-gpu-kernel-generation-via-deep-agents/
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L1/— selected Level 1 problems (original + generated Triton kernel). -
L2/— selected Level 2 problems (original + generated Triton kernel). -
L3/— selected Level 3 problems:-
Fuser route: original + fused.py + subgraphs.json + per-subgraph kernels + composed_kernel.py + verify logs.
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KernelAgent route: original + final_kernel.py + test.py + result.json.
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kernelfalcon-artifacts/— tiny examples for quick browsing.
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L1-examples/matmul/— original + generated Triton kernel + short PASS log. -
L2-examples/conv-bn-relu/— original + generated Triton kernel (KernelAgent route). -
L3-examples/resnet-block/— input_model + subgraphs.json + composed_kernel + verify log (Fuser route).
Artifacts were produced using the KernelAgent repo: https://github.com/meta-pytorch/KernelAgent
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Auto-router:
python -m Fuser.auto_agent --problem <abs/path/to/problem.py> --verify -
Full pipeline:
python -m Fuser.pipeline --problem <abs/path> --extract-model gpt-5 --dispatch-model o4-mini --compose-model o4-mini --dispatch-jobs auto --verify -
KernelAgent direct (Python): see
triton_kernel_agentin the main repo.
Each example folder contains a manifest.json with route, files, and verification info.
We trimmed logs for readability; full run artifacts live under .fuse/run_* and agent sessions in the main workspace and can be reproduced with the commands above.
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Kernels here are Triton implementations (no PyTorch compute helpers in wrappers).
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Verification gates success on execution-based checks with tolerances (default rtol=1e-3, atol=1e-3; caps for fp16/bf16 at 1e-2).