Individual skill
vectorize-triton-ascend-comparisons
Vectorize explicit integer comparisons in Triton-Ascend by casting bounded index vectors to float32 before tl.where or similar compute expressions. Use when an agent observes scalarized int32 or int64 comparison code on Ascend NPU, especially in LayerNorm tail handling, while load/store masks already compile efficiently.
skills/vectorize-triton-ascend-comparisons/SKILL.md
Source commit 4ab5ee7adf47755ecd42723f55f4c58e38be95a7
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- Instructions only
- Last checked
- Nov 4, 2026
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- Repository last updated
- Aug 15, 2026
- License
- 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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# Vectorize Triton-Ascend Comparisons
## Goal
Move eligible explicit comparisons onto Ascend vector cast and compare instructions without changing mask semantics.
## Workflow
1. Identify comparisons used in compute expressions such as tl.where, not only load/store masks.
2. Prove that all compared integer values are exactly representable in float32.
3. Cast the index vector to tl.float32 immediately before the comparison.
4. Keep original integer offsets for pointer arithmetic and memory masks.
5. Inspect performance and compare results around the tail boundary.
