Individual skill
max-autotune-triton-ascend
Apply Triton-Ascend max_autotune to search base kernel configurations together with Ascend compiler options for vector, cube, or mixed operators. Use when an agent needs multi-parameter performance tuning without manually enumerating every triton.Config combination, must choose kernel_type, or must constrain compiler-option search lists such as num_stages and enable_ubuf_saving.
skills/max-autotune-triton-ascend/SKILL.md
Source commit 4ab5ee7adf47755ecd42723f55f4c58e38be95a7
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Instructions only
- Last checked
- Nov 4, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 189
- Repository last updated
- Aug 15, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai Repository topic
- ascend Repository topic
- ascend-npu Repository topic
- npu Repository topic
- triton Repository topic
- triton-ascend Repository topic
- claude-code Repository topic
- codex Repository topic
- opencode Repository topic
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
# Max-Autotune Triton-Ascend
## Goal
Expand a small set of kernel meta-parameter configurations into a controlled search over Ascend compiler options.
## Workflow
1. Verify the kernel and PyTorch reference before tuning.
2. Import max_autotune from triton.backends.ascend.runtime.
3. Provide a small base configs list containing only meaningful kernel meta-parameters.
4. Set key to runtime values whose changes may require a new winner.
5. Classify the kernel as vector, cube, or mix.
6. Add short explicit option lists only when the built-in search space is unsuitable.