Individual skill
fuse-triton-ascend-cat-conv1d
Refactor fused causal Conv1d state updates for Triton-Ascend by replacing negative-offset cat emulation and tl.where selection with transposed UB assembly through extension.insert_slice. Use when an agent ports causal_conv1d_update-style kernels, sees discrete scalar loads from negative offsets, suffers 32-byte tail-axis padding, or launches far more logical tasks than Ascend vector cores.
skills/fuse-triton-ascend-cat-conv1d/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
# Fuse Triton-Ascend Cat and Causal Conv1d
## Goal
Join convolution state and new tokens in UB, update the cached tail, and compute grouped causal Conv1d without materializing a global concatenation.
## Workflow
1. Preserve the reference contract for x, conv_state, depthwise weights, bias, activation, and state-row indices.
2. Load state and input from nonnegative contiguous addresses.
3. Transpose or reshape them so concatenation occurs along a contiguous flattened UB axis.
4. Insert state followed by new tokens with extension.insert_slice.
5. Derive the new state tail and convolution windows from the assembled tensor.
6. Map work to approximately the available vector-core count and loop over remaining feature tiles inside each program.