profiling-tilelang-programs
profiling-tilelang-programs is a Runtime diagnostics & profiling skill for AI agents, published by sablin39 in the tilelang-cuda-skills repository on GitHub. Skillspace rates profiling-tilelang-programs D (66/100) and it passed the safety scan; the rating is based on static analysis only.
How to benchmark and profile TileLang GPU kernels for performance measurement. Use this skill whenever the user wants to measure kernel latency, compare TileLang performance against PyTorch/cuBLAS/Triton, use do_bench or get_profiler, calculate TFLOPS or bandwidth, run Nsight Compute or Nsight Systems on a TileLang kernel, understand occupancy or shared memory usage, or figure out why a kernel is slow. Also trigger when the user mentions benchmarking, profiling, timing, throughput, performance numbers, or latency in the context of TileLang or GPU kernels. Even for simple questions like "how fast is my kernel" or "how do I time this".
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 131
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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