# nemo-mbridge-perf-moe-comm-overlap

A skill for MoE expert-parallel communication overlap in Megatron Bridge: dispatch/combine, flex dispatcher backends, expert wgrad scheduling.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1800 installs · ★ 3735
- Author: NVIDIA
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/NVIDIA/skills/tree/HEAD/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/nemo-mbridge-perf-moe-comm-overlap

## What it does

The skill covers turning on MoE communication overlap in Megatron Bridge and tracing a throughput regression back to a comm-overlap config change. It ships a quick decision check, the prerequisite list, notes on how overlap interacts with recompute and CUDA graphs, and measured runs on Qwen3 30B-A3B.

Enablement is config work: `cfg.comm_overlap.overlap_moe_expert_parallel_comm = True`, optionally `cfg.comm_overlap.delay_wgrad_compute = True`, and `cfg.model.moe_shared_expert_overlap` set to `False`. You need `expert_model_parallel_size > 1`, `num_moe_experts > 1`, a dispatcher type of `"alltoall"` or `"flex"`, and BF16 or FP16 precision. With pipeline parallelism active, VPP is required. Setting `moe_flex_dispatcher_backend` on its own does nothing — flex dispatch also needs `moe_token_dispatcher_type = "flex"`.

Full recompute pairs badly with this path, so selective recompute is the safer choice. Validation is straightforward: the check in `comm_overlap.py` raises when prerequisites are not met, so a clean startup means the feature is live. A 16-H100 run cut step time by 15.059% and raised throughput by 17.729%, though the authors note the gain is workload-dependent and a small or lightly loaded EP run may see nothing.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-moe-comm-overlap -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/nemo-mbridge-perf-moe-comm-overlap/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-moe-comm-overlap -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-moe-comm-overlap -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install NVIDIA/skills nemo-mbridge-perf-moe-comm-overlap
```

2. **Manually: put the files in place**
- File: `.github/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-moe-comm-overlap -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/NVIDIA/skills --path skills/nemo-mbridge-perf-moe-comm-overlap
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-moe-comm-overlap -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/NVIDIA/skills/tree/HEAD/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md

## When to use it
- turn on dispatch and combine overlap for expert-parallel MoE
- trace a throughput drop back to a comm-overlap config change
- work out why flex dispatch stays off after setting the backend flag
- pair overlap with a recompute plan and CUDA-graph scopes
- check prerequisites before committing to a full run

## Example prompts
- Enable overlap_moe_expert_parallel_comm and verify the prerequisites hold
- Throughput dropped after my config change — check whether comm overlap is involved
- Why is flex dispatch not active when I set moe_flex_dispatcher_backend

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 9031304f9f266b3f.

BEGIN THIRD-PARTY FILE 9031304f9f266b3f
````text
---
name: nemo-mbridge-perf-moe-comm-overlap
description: MoE expert-parallel communication overlap in Megatron Bridge. Covers dispatch/combine overlap, flex dispatcher backends, and expert wgrad scheduling.
license: Apache-2.0
when_to_use: Tuning MoE communication overlap, or tracing a MoE throughput regression to a comm-overlap config change; 'overlap_moe_expert_parallel_comm', 'MoE dispatch overlap', 'flex dispatcher', 'DeepEP overlap', 'expert wgrad scheduling'.
---

# MoE Communication Overlap

For the higher-level overview, see:

- @docs/training/communication-overlap.md
- @skills/nemo-mbridge-perf-moe-comm-overlap/card.yaml

## Quick Decision

Use MoE communication overlap when:

- `EP > 1`
- token dispatch or combine time is visible in the profile

Avoid turning it on as an early bring-up step. It is easier to validate after
the dispatcher, routing mode, and recompute plan are already stable.

## Enablement

```python
cfg.comm_overlap.overlap_moe_expert_parallel_comm = True

# Optional: delayed wgrad for additional overlap
cfg.comm_overlap.delay_wgrad_compute = True

# IMPORTANT: disable shared expert overlap when using dispatch overlap
cfg.model.moe_shared_expert_overlap = False
```

### Prerequisites

- `expert_model_parallel_size > 1`
- `num_moe_experts > 1`
- `moe_token_dispatcher_type` must be `"alltoall"` or `"flex"`
- Precision: BF16 or FP16
- If PP is used, VPP (`virtual_pipeline_model_parallel_size`) must be set (non-`None`)

### Flex dispatcher activation

Setting `moe_flex_dispatcher_backend` alone does **not** activate flex dispatch.
You must also set `moe_token_dispatcher_type = "flex"`.

## Recompute And CUDA Graph Interaction

- Full recompute is not a good companion for the overlap path.
- `delay_wgrad_compute` adds further constraints if CUDA-graph scopes include
  attention or MoE-router work.
- In practice, selective recompute is the safer pairing when overlap is enabled.

## Measured Evidence

### HybridEP production-shape validation

A 2026-07-25 controlled Qwen3 30B-A3B pretraining comparison used 16 H100
GPUs, BF16, sequence length 4096, `TP=1`, `PP=1`, `CP=1`, `EP=16`,
````
END THIRD-PARTY FILE 9031304f9f266b3f

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First 2137 of 7426 bytes. © NVIDIA · Apache-2.0 · https://github.com/NVIDIA/skills/tree/HEAD/skills/nemo-mbridge-perf-moe-comm-overlap/SKILL.md

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