ascend-triton-kernel-optimization · git:20260911.9f92063 · 2026-09-11 · sha256 222fee1e8b93b581
ascend-triton-kernel-optimization git:20260911.9f92063A
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--- 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 using the platform's Python launcher. The workspace selects its installed platform environment automatically. ```text 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. Read the relevant detail only when needed: - [behavior](references/behavior.md) - [profiling decision tree](references/profiling-decision-tree.md) - [ascend techniques](references/ascend-techniques.md)