Agent skill

Triton Kernel

Write optimized Triton GPU kernels for deep learning operations.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Triton Kernel

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a claude-code

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

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel --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/vipshop/cache-dit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/triton-kernel .claude/skills/triton-kernel && 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/

Paste into Claude Code

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .claude/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/vipshop/cache-dit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/triton-kernel .agents/skills/triton-kernel && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .agents/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/vipshop/cache-dit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/triton-kernel .cursor/skills/triton-kernel && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .cursor/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/vipshop/cache-dit.git --path .github/skills/triton-kernel

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/vipshop/cache-dit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/triton-kernel .gemini/skills/triton-kernel && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .gemini/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/vipshop/cache-dit.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/triton-kernel .github/skills/triton-kernel && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .github/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add vipshop/cache-dit --skill triton-kernel -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install vipshop/cache-dit triton-kernel --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/vipshop/cache-dit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/triton-kernel .opencode/skills/triton-kernel && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "triton-kernel" agent skill from https://github.com/vipshop/cache-dit/tree/main/.github/skills/triton-kernel into .opencode/skills/triton-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "triton-kernel", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: triton-kernel
GitHub stars: 1.3k
Token cost: ~1.1k tokens
SKILL.md length: 372 words
Files: 11
Skills in repo: 7
Repo updated: Sep 29, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Write optimized Triton GPU kernels for deep learning operations.

Tasks that involve GPU and accelerator computing
SKILL.md covers Core Patterns (always apply), Quick Reference Examples, Performance Bottleneck… and Specialized Topics, plus 1 more section
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Tasks that involve Deep learning

What it does

Triton Kernel is an agent skill from vipshop/cache-dit. Write optimized Triton GPU kernels for deep learning operations. Covers the full spectrum from basic vector ops to Flash Attention, persistent matmul, fused normalization, quantized GEMM, and memory-efficient patterns.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files (for example `triton-dynamic-launcher-tiling.md`, `triton-flash-attention-v2.md` and `triton-fused-epilogue-kernels.md`).

It sits in AI & LLM Engineering, covering GPU and accelerator computing, Deep learning and Database schema design. The repository describes itself as: A PyTorch-native inference engine with cache, parallelism, quantization and cpu offload for DiTs. The licence is Apache-2.0.

When your agent uses it

Tasks that involve GPU and accelerator computing
Tasks that involve Deep learning
Tasks that involve Database schema design

Example prompts

“/triton-kernel”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit a7898aa. 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

Triton Kernel loads about 1.1k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 372 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~58
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k

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 vipshop/cache-dit at commit a7898aa, republished under its Apache-2.0 licence (© vipshop). 372 words, ~1,131 tokens.

Download SKILL.mdSave it as .claude/skills/triton-kernel/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.

name: triton-kernel
description: Write optimized Triton GPU kernels for deep learning operations. Covers the full spectrum from basic vector ops to Flash Attention, persistent matmul, fused normalization, quantized GEMM, and memory-efficient patterns.
user-invocable: true

Writing Optimized Triton GPU Kernels

Targets: Triton >= 2.1, any GPU with tl.dot support (SM70+/CDNA2+)

Core Patterns (always apply)

Kernel structure: Use @triton.jit decorator. Get block ID with tl.program_id(axis). Compute element offsets with tl.arange(0, BLOCK_SIZE). Build mask = offsets < n_elements for all loads/stores.

Block sizes: Strongly prefer powers of two (required for tl.arange; non-power-of-two may work but can reduce performance). Declare as tl.constexpr parameters. Use @triton.autotune to sweep BLOCK_SIZE_M/N/K configs per hardware.

Memory hierarchy: Keep intermediates in SRAM via block-level reductions (tl.sum, tl.max) before writing to global memory. Fuse multiple pointwise ops into one kernel to avoid DRAM round-trips.

Matmul: Use tl.dot(a, b) for tensor core operations. Always accumulate in tl.float32 when inputs are FP16. For L2 cache locality, use grouped tile ordering via group_id = pid // GROUP_SIZE.

Grid launching: Size grid dynamically: grid = lambda meta: (triton.cdiv(n, meta['BLOCK_SIZE']),).

Masking: ALWAYS mask boundary loads/stores: tl.load(ptr + offs, mask=offs < dim, other=0.0). Missing masks corrupt memory silently.

Benchmarking: Use triton.testing.Benchmark with x_names, x_vals, line_arg, line_vals to compare against PyTorch baselines.

Quick Reference Examples

Fused row-wise softmax — verified, based on official Triton tutorial:

python

@triton.jit
def fused_softmax(x_ptr, out_ptr, cols, BLOCK: tl.constexpr):
    row = tl.program_id(0)
    offs = tl.arange(0, BLOCK)
    mask = offs < cols
    x = tl.load(x_ptr + row * cols + offs, mask=mask, other=-1e9)
    x_max = tl.max(x, axis=0)
    ex = tl.exp(x - x_max)
    out = ex / tl.sum(ex, axis=0)
    tl.store(out_ptr + row * cols + offs, out, mask=mask)

Seed-based dropout — verified, based on official Triton tutorial:

python

@triton.jit
def dropout(x_ptr, out_ptr, seed, p, n, BLOCK: tl.constexpr):
    offs = tl.program_id(0) * BLOCK + tl.arange(0, BLOCK)
    mask = offs < n
    x = tl.load(x_ptr + offs, mask=mask)
    r = tl.rand(seed, offs)  # Philox PRNG, deterministic
    keep = r > p
    tl.store(out_ptr + offs, x * keep / (1.0 - p), mask=mask)

Performance Bottleneck Quick-Reference

When optimizing an existing kernel, classify the bottleneck first (profile with ncu):

Bottleneck	Diagnosis	Fix
Memory-bound	DRAM throughput > 60% of peak, compute < 30%	PID swizzle, TMA, fuse ops to reduce loads
Compute-bound	Tensor core utilization > 60%, DRAM < 40%	Persistent kernels, increase `num_stages`, warp specialization
Underutilized	Both < 60%, high stall metrics	Reduce register pressure, increase `num_warps`, autotune

See triton-gpu-kernel-optimization.md for specific NCU metric names and detailed strategies.

Show full SKILL.md (120 more words)Show less

Specialized Topics

Read these files for detailed guidance when the task involves these areas:

Task	File to read
Flash Attention / fused self-attention	`triton-flash-attention-v2.md`
Persistent kernels, warp specialization, TMA	`triton-persistent-warp-matmul.md`
LayerNorm, RMSNorm, GroupNorm (fwd + bwd)	`triton-fused-normalizations.md`
FP4/FP8 quantized matmul, block scaling	`triton-quantized-block-scaled-gemm.md`
Kernel fusion, Philox dropout, recomputation	`triton-memory-efficient-patterns.md`
General tiled GEMM, autotune, benchmarking	`triton-gpu-kernel-optimization.md`
Fusing normalization/gating/residual into attention or matmul epilogue	`triton-fused-epilogue-kernels.md`
Sequential stateful processing (LRU routing, mutable register state)	`triton-sequential-stateful-blocks.md`
Launcher tile selection, num_stages/num_warps heuristics	`triton-dynamic-launcher-tiling.md`

When to read specialized files: Only read the relevant file when the user's task specifically involves that topic. The core patterns above are sufficient for basic kernels (vector ops, elementwise fusion, simple reductions).

Other references

triton-opt.md: For general optimization techniques while writing triton kernels.

Files

SKILL.md and 10 other files in .github/skills/triton-kernel of vipshop/cache-dit.

SKILL.md
triton-dynamic-launcher-tiling.md
triton-flash-attention-v2.md
triton-fused-epilogue-kernels.md
triton-fused-normalizations.md
triton-gpu-kernel-optimization.md
triton-memory-efficient-patterns.md
triton-opt.md
triton-persistent-warp-matmul.md
triton-quantized-block-scaled-gemm.md
triton-sequential-stateful-blocks.md

Open the folder on GitHubat commit a7898aa

Compare with similar skills

Triton Kernel 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.

Triton Kernel compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Triton Kernel this skillvipshop/cache-dit	1.3k	—	~1.1k	Automated safety check: Pass	Apache-2.0	10 days ago
MUSA GPU Training Optimizeropen-infra-skills/infra-skills	141	—	~1.7k	Automated safety check: Pass	Apache-2.0	3 mo ago
PyTorch Lightning TrainingOrchestra-Research/AI-Research-SKILLs	13k	6 repos	~2.3k	Automated safety check: Pass	MIT	3 mo ago
Megatron-LM on SLURMNVIDIA/Megatron-LM	18k	—	~1.8k	Automated safety check: Pass	Apache-2.0	today
DGX Spark Training Gotchaswshobson/agents	40k	—	~2k	Automated safety check: Pass	MIT	4 days ago
Hugging Face AccelerateOrchestra-Research/AI-Research-SKILLs	13k	5 repos	~2.1k	Automated safety check: Pass	MIT	3 mo ago

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Questions about Triton Kernel

What does Triton Kernel do?

Write optimized Triton GPU kernels for deep learning operations. Triton Kernel is an agent skill from vipshop/cache-dit. Write optimized Triton GPU kernels for deep learning operations.

When should I use Triton Kernel?

Triton Kernel fits situations like: tasks that involve GPU and accelerator computing; tasks that involve Deep learning; tasks that involve Database schema design.

How do I install Triton Kernel in Claude Code?

Run `npx skills add vipshop/cache-dit --skill triton-kernel -a claude-code`. Or copy the skill folder (.github/skills/triton-kernel in vipshop/cache-dit) into .claude/skills/triton-kernel in your project. Claude Code loads it when a task matches its description.

How do I install Triton Kernel in Codex?

Run `npx skills add vipshop/cache-dit --skill triton-kernel -a codex`. Or copy the skill folder (.github/skills/triton-kernel in vipshop/cache-dit) into .agents/skills/triton-kernel in your project. Codex loads it when a task matches its description.

Can I use Triton Kernel 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 vipshop/cache-dit --skill triton-kernel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/triton-kernel, .gemini/skills/triton-kernel, .github/skills/triton-kernel and .opencode/skills/triton-kernel in your project.

What does Triton Kernel need to run?

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

Does Triton Kernel 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 Triton Kernel 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 Triton Kernel use?

Triton Kernel 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 Triton Kernel use?

About 1.1k tokens (SKILL.md is roughly 4.5k 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 Triton Kernel?

Skills that share tags, products or a category with Triton Kernel: MUSA GPU Training Optimizer (open-infra-skills/infra-skills, 141 stars), PyTorch Lightning Training (Orchestra-Research/AI-Research-SKILLs, 13k stars), Megatron-LM on SLURM (NVIDIA/Megatron-LM, 18k stars) and DGX Spark Training Gotchas (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Triton Kernel?

vipshop (a GitHub organization) maintains it in vipshop/cache-dit, which has 1,289 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 29, 2026.

Source: vipshop/cache-dit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Triton Kernel

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Writing Optimized Triton GPU Kernels

Core Patterns (always apply)

Quick Reference Examples

Performance Bottleneck Quick-Reference

Specialized Topics

Other references

Files

Compare with similar skills

Similar skills

More from vipshop/cache-dit

Related

Questions about Triton Kernel