torch-profiling-tilelang-programs

torch-profiling-tilelang-programs is an MLOps & model serving skill for AI agents, published by sablin39 in the tilelang-cuda-skills repository on GitHub. Skillspace rates torch-profiling-tilelang-programs C (72/100) and it passed the safety scan; the rating is based on static analysis only.

Use torch.profiler as a lightweight, always-available alternative to Nsight Compute/Systems for profiling, debugging, and optimizing TileLang GPU kernels. Trigger this skill whenever the user wants to profile a TileLang kernel without installing ncu/nsys, get an operator/kernel breakdown of a forward pass that includes TileLang custom ops, hunt launch-overhead in a multi-kernel pipeline, classify whether a TileLang kernel is IO-bound / CUDA-core bound / Tensor-core bound, generate a Chrome trace, profile GPU memory allocations, or compare a TileLang kernel against a torch/cuBLAS reference inside one trace. Also trigger on phrases like "profile this kernel", "why is this slow", "how do I see the kernel timeline", "lightweight profiling", "torch profiler", "chrome trace", or "perfetto", even if the user does not mention TileLang explicitly but TileLang code is on the table.

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

131

Unproven: rated by static analysis only, not yet compared head-to-head.

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