---
name: ascend-triton-kernel-optimization
description: Profile and iteratively optimize a correctness-passed Ascend Triton kernel with explicit NPU baselines, per-shape measurements, UB live-set and physical-core reasoning, MTE/Vector/Scalar bottleneck attribution, one-hypothesis rounds, noise-aware KEEP/DISCARD decisions, and Run Manifest evidence. Use for single-kernel latency or throughput improvement after all planned correctness cases pass. Do not use to create or migrate the first correct kernel, bypass failed validation, assess whole-model serving regressions, attribute model HBM, or diagnose a non-Triton operator.
---

# ascend-triton-kernel-optimization

Optimize an already validated Ascend Triton kernel using measured bottlenecks and repeatable latency evidence.

Choose one bottleneck hypothesis per round. Consider UB live set, physical cores and MTE/Vector/Scalar overlap. Compare repeated per-shape measurements with a reference baseline; retain a change only when the gain exceeds noise and correctness still covers the candidate.

## Agent entry

Run from the repository root. The entry reuses the installed platform environment.

```text
uv run --no-project python .agents/skills/ascend-triton-kernel-optimization/scripts/triton_optimization.py --config optimization.json --results round-results.json
```

The config contains op_name, kernel and its validation evidence, target, cases, baseline measurements and objective. Round results carry candidate measurements and validation. The report computes KEEP/DISCARD and verifies kernel lineage and case coverage.

Use ascend-triton-kernel-validation when correctness is incomplete. Use profiling-analysis for whole-model performance attribution.

The report aggregates supplied evidence. Imported numerical results and latency
measurements do not by themselves prove candidate NPU execution; this remains
unknown in the aggregate status. Keep the measured outcomes and use existing
runner or profiler evidence in the task assessment. That report limitation adds
no prerequisite for work already supported by valid execution evidence.

Read the relevant detail only when needed:

- [profiling decision tree](references/profiling-decision-tree.md)
- [ascend techniques](references/ascend-techniques.md)