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Agent skill

Build Triton Ascend Moe Gather Scatter

by Krusty84 in Krusty84/triton-ascend-agent-dev-kit

Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Build Triton Ascend Moe Gather Scatter

skills CLI
$ npx skills add Krusty84/triton-ascend-agent-dev-kit --skill build-triton-ascend-moe-gather-scatter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Krusty84/triton-ascend-agent-dev-kit build-triton-ascend-moe-gather-scatter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Krusty84/triton-ascend-agent-dev-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/build-triton-ascend-moe-gather-scatter .claude/skills/build-triton-ascend-moe-gather-scatter && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
build-triton-ascend-moe-gather-scatter
GitHub stars
106
Token cost
~696 tokens
SKILL.md length
252 words
Files
1
Skills in repo
23
Repo updated
First seen
Licence
Apache-2.0

At a glance

Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions.

  • Works in 6 steps: Define L = tokens * TOP_K and require… → Gather routed row i from token row… → Scatter routed row i into assignment… → …
  • An agent ports MegaBlocks-style unbinned token routing to Triton-Ascend
  • SKILL.md covers Goal, Workflow, Implementation Pattern and Ascend Guardrails, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Build Triton Ascend Moe Gather Scatter is an agent skill from Krusty84/triton-ascend-agent-dev-kit. Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions. Use when an agent ports MegaBlocks-style unbinned token routing to Triton-Ascend, reorders top-k token assignments, combines weighted expert outputs, or computes per-route weight gradients.

Its SKILL.md is about 700 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering. The repository describes itself as: A toolkit for AI agents used for development on Triton-Ascend for Ascend NPU. The licence is Apache-2.0.

When your agent uses it

  • An agent ports MegaBlocks-style unbinned token routing to Triton-Ascend
  • Reorders top-k token assignments
  • Combines weighted expert outputs
  • Computes per-route weight gradients

Example prompts

  • “/build-triton-ascend-moe-gather-scatter”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Define L = tokens * TOP_K and require indices to be a permutation of assignment IDs in [0, L).
  2. Gather routed row i from token row indices[i] // TOP_K.
  3. Scatter routed row i into assignment slot indices[i], optionally scale by weights[indices[i]], then reduce the TOP_K slots per token.
  4. Compute wgrad[indices[i]] as the float32 dot product of routed row i and grads[indices[i] // TOP_K].
  5. Split L approximately evenly across the target vector cores.
  6. Process SUB_BLOCK_SIZE assignments and BLOCK_X feature columns at a time.

What it can do on your machine

Read from SKILL.md and the folder at commit 4ab5ee7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Build Triton Ascend Moe Gather Scatter loads about 696 tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 252 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~696

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Krusty84/triton-ascend-agent-dev-kit at commit 4ab5ee7, republished under its Apache-2.0 licence (© Krusty84). 252 words, ~696 tokens.

Download SKILL.mdSave it as .claude/skills/build-triton-ascend-moe-gather-scatter/SKILL.md (or your agent's skills folder).
name
build-triton-ascend-moe-gather-scatter
description
Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions. Use when an agent ports MegaBlocks-style unbinned token routing to Triton-Ascend, reorders top-k token assignments, combines weighted expert outputs, or computes per-route weight gradients.

Build Triton-Ascend MoE Gather and Scatter

Goal

Implement the unbinned routing triplet over assignment IDs: gather token rows into routing order, scatter weighted rows back to tokens, and compute one router-weight gradient per assignment.

Workflow

  1. Define L = tokens * TOP_K and require indices to be a permutation of assignment IDs in [0, L).
  2. Gather routed row i from token row indices[i] // TOP_K.
  3. Scatter routed row i into assignment slot indices[i], optionally scale by weights[indices[i]], then reduce the TOP_K slots per token.
  4. Compute wgrad[indices[i]] as the float32 dot product of routed row i and grads[indices[i] // TOP_K].
  5. Split L approximately evenly across the target vector cores.
  6. Process SUB_BLOCK_SIZE assignments and BLOCK_X feature columns at a time.

Implementation Pattern

python
num_cores = get_npu_properties()["num_vectorcore"]
rows_per_core = triton.cdiv(indices.numel(), num_cores)
block_x = round_up_to_16(min(hidden_size, max_block_x))
sub_block = choose_from_ub_budget(block_x, live_buffers)
kernel[(num_cores,)](
    x, out, indices,
    INDICES_LENGTH=indices.numel(),
    BLOCK_SIZE=rows_per_core,
    SUB_BLOCK_SIZE=sub_block,
    NUM_COLUMNS=hidden_size,
    BLOCK_X=block_x,
    TOP_K=top_k,
    multibuffer=True,
)

Inside gather, assemble SUB_BLOCK_SIZE rows with extension.insert_slice before a contiguous store. Inside scatter, load a contiguous routed tile and use extension.extract_slice for unique indexed stores.

Ascend Guardrails

  • Import extension from triton.language.extra.cann.extension.
  • Align BLOCK_X to 16 elements for 32-byte fp16/bfloat16 alignment.
  • Derive SUB_BLOCK_SIZE from all UB-resident indices, input tiles, output tiles, float32 temporaries, and multibuffer copies.
  • Set SUB_BLOCK_SIZE=1 when hidden-size column tiling requires accumulation across multiple BLOCK_X tiles.
  • Require unique assignment IDs before non-atomic scatter stores.
  • Apply optional weights by assignment ID, not routed-row position.
  • Accumulate scaling and gradient dot products in float32, then cast once on store.

Verification

Compare all three operations with a NumPy or PyTorch loop. Cover TOP_K=1 and greater, random routing permutations, weighted and unweighted scatter, small unaligned hidden sizes, large column-tiled hidden sizes, and multiple token/expert counts.

© Krusty84, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/build-triton-ascend-moe-gather-scatter of Krusty84/triton-ascend-agent-dev-kit.

Open the folder on GitHubat commit 4ab5ee7

Compare with similar skills

Build Triton Ascend Moe Gather Scatter next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
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1passwordtrpc-group/trpc-agent-go1.9k14 repos~656Automated safety check: PassApache-2.0

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Categories

Questions about Build Triton Ascend Moe Gather Scatter

What does Build Triton Ascend Moe Gather Scatter do?

Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions. Build Triton Ascend Moe Gather Scatter is an agent skill from Krusty84/triton-ascend-agent-dev-kit. Build Ascend-friendly MoE gather, scatter, and router-weight-gradient kernels with vector-core-sized grids, UB-aware row/column tiling, and CANN slice extensions.

When should I use Build Triton Ascend Moe Gather Scatter?

Build Triton Ascend Moe Gather Scatter fits situations like: an agent ports MegaBlocks-style unbinned token routing to Triton-Ascend; reorders top-k token assignments; combines weighted expert outputs; computes per-route weight gradients.

How do I install Build Triton Ascend Moe Gather Scatter in Claude Code?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill build-triton-ascend-moe-gather-scatter -a claude-code`. Or copy the skill folder (skills/build-triton-ascend-moe-gather-scatter in Krusty84/triton-ascend-agent-dev-kit) into .claude/skills/build-triton-ascend-moe-gather-scatter in your project. Claude Code loads it when a task matches its description.

How do I install Build Triton Ascend Moe Gather Scatter in Codex?

Run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill build-triton-ascend-moe-gather-scatter -a codex`. Or copy the skill folder (skills/build-triton-ascend-moe-gather-scatter in Krusty84/triton-ascend-agent-dev-kit) into .agents/skills/build-triton-ascend-moe-gather-scatter in your project. Codex loads it when a task matches its description.

Can I use Build Triton Ascend Moe Gather Scatter in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Krusty84/triton-ascend-agent-dev-kit --skill build-triton-ascend-moe-gather-scatter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/build-triton-ascend-moe-gather-scatter, .gemini/skills/build-triton-ascend-moe-gather-scatter, .github/skills/build-triton-ascend-moe-gather-scatter and .opencode/skills/build-triton-ascend-moe-gather-scatter in your project.

What does Build Triton Ascend Moe Gather Scatter need to run?

SKILL.md names no scripts, command-line tools or credentials: Build Triton Ascend Moe Gather Scatter is instructions for the agent only. Our summary lists: Python 3.

Does Build Triton Ascend Moe Gather Scatter access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Build Triton Ascend Moe Gather Scatter safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Build Triton Ascend Moe Gather Scatter use?

Build Triton Ascend Moe Gather Scatter is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Build Triton Ascend Moe Gather Scatter use?

About 696 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Build Triton Ascend Moe Gather Scatter?

Skills that share tags, products or a category with Build Triton Ascend Moe Gather Scatter: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Build Triton Ascend Moe Gather Scatter?

Krusty84 (a GitHub user) maintains it in Krusty84/triton-ascend-agent-dev-kit, which has 106 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on August 15, 2026.

Source: Krusty84/triton-ascend-agent-dev-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.