Individual skill
rank-triton-ascend-costmodel
Generate TTIR for Triton-Ascend kernel configurations and rank them with the Ascend costmodel backend before empirical autotuning. Use when an agent needs to prefilter a large configuration space, construct costmodel_bench items, bind runtime TTIR arguments or program IDs, or interpret predicted latency values.
skills/rank-triton-ascend-costmodel/SKILL.md
Source commit 4ab5ee7adf47755ecd42723f55f4c58e38be95a7
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- Aug 15, 2026
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- Apache-2.0
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- 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
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# Rank Triton-Ascend Configs with Costmodel
## Goal
Predict latency for several compile-time kernel configurations and retain the most promising candidates for real correctness checks and benchmarking.
## Workflow
1. Define the Triton kernel, pointer/runtime signature, and candidate constexpr values.
2. Build a separate ASTSource and TTIR string for every candidate.
3. Enable the costmodel backend in Ascend compiler options.
4. Create one item per candidate with a unique config name, TTIR, and optional arg_bindings.
5. Call costmodel_bench, sort the returned microsecond predictions, and shortlist candidates.
6. Verify and benchmark the shortlist on real NPU inputs.