FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
- 198198 likes
- 103103 saves
Works with
- Claude Code
- Codex
- Cursor
- and 3 more
Iterative cuTile kernel optimization v1.0.0
Use this resource to iteratively improve the performance of a cuTile kernel in TileGym
New
- 389 downloads
- 117 likes
- 141 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install cutile-kernel-performance-optimizationWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent creates an experiment branch, sets a baseline, then loops: change one knob, measure, log. It covers tile sizes, occupancy, autotune, TMA, persistent scheduling, num_ctas and IR analysis. You get an experiment log and a faster kernel.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- CC-BY-4.0
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What you get
- references/optimization-playbook.md: optimization method
- references/perf-knobs-catalog.md: knob catalog
- references/ir-dump-guide.md: IR reading guide
Good fit for
- A TileGym kernel is slower than expected
- You want every tuning trial recorded in a log
Not for
Tags
- cuTile
- optimization
- GPU
- profiling
About
You say
“Optimize the cuTile kernel my_op: measure the baseline, then try different tile sizes.”
Skill published by nvidia under the CC-BY-4.0 license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to iteratively improve the performance of a cuTile kernel in TileGym
- Review and adjust the result
Content preview
Files
- BENCHMARK.md3.6 KB
- evals/evals.json5.3 KB
- LICENSE11.3 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/cutile-api-reference.md31.3 KB
- references/cutile-patterns-reference.md7.8 KB
- references/ir-dump-guide.md8.1 KB
- references/optimization-playbook.md15.2 KB
- references/perf-knobs-catalog.md6.7 KB
- references/performance-model.md19.2 KB
- skill-card.md4.3 KB
- SKILL.md7.8 KB
- skill.oms.sig6 KB
Origin and licence
Listed unmodified
- Author
- nvidia
- Source
- github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tilegym-improve-cutile-kernel-perf
- Licence
- CC-BY-4.0
Notice
« tilegym-improve-cutile-kernel-perf » (nvidia, CC-BY-4.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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