# nemo-mbridge-perf-megatron-fsdp

Configures Megatron FSDP in Megatron-Bridge to replace standard DDP, helping resolve out-of-memory errors and verify training checkpoints.

- 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-megatron-fsdp/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/nemo-mbridge-perf-megatron-fsdp

## What it does

This skill guides developers through enabling Megatron Fully Sharded Data Parallel in Megatron-Bridge. It details the required configuration flags, including `cfg.dist.use_megatron_fsdp = True`, `data_parallel_sharding_strategy = "optim_grads_params"`, and setting `average_in_collective = False`. It also points to code anchors in `src/megatron/bridge/training/config.py` and benchmark harness flags.

Checkpoint configuration is a frequent failure point. Default training recipes fall back to `torch_dist`, while Megatron FSDP requires `fsdp_dtensor`. Megatron FSDP cannot run alongside `use_torch_fsdp2` or `use_tp_pp_dp_mapping`. CPU offloading is permitted only when `pipeline_model_parallel_size == 1` and activation recomputation is turned off.

Verification relies on a 2-GPU functional smoke test executed via PyTorch distributed run and Pytest. A clean run finishes with finite loss on the final step and encounters zero checkpoint assertions.

## Install

### Claude Code (native platform)

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

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

### Codex

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

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

### Cursor

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

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

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install NVIDIA/skills nemo-mbridge-perf-megatron-fsdp
```

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

### Gemini CLI

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

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

### Windsurf (Devin Desktop)

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

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add NVIDIA/skills --skill nemo-mbridge-perf-megatron-fsdp -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-megatron-fsdp/SKILL.md

## When to use it
- switch from standard DDP to Megatron FSDP in Megatron-Bridge
- resolve checkpoint assertions by configuring fsdp_dtensor
- avoid out-of-memory errors during large language model pretraining
- verify multi-GPU FSDP runs with the built-in Pytest smoke test

## Example prompts
- Configure my Megatron-Bridge training recipe to use Megatron FSDP
- Fix checkpoint format assertion errors when saving Megatron FSDP weights
- Run the 2-GPU functional verification test for Megatron FSDP

## 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: 386972385200cd55.

BEGIN THIRD-PARTY FILE 386972385200cd55
````text
---
name: nemo-mbridge-perf-megatron-fsdp
description: Operational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
license: Apache-2.0
when_to_use: Using FSDP-based data parallelism instead of DDP, or tracing an OOM or regression to a FSDP config change; 'use_megatron_fsdp', 'data_parallel_sharding_strategy', 'sharded data parallel', 'Megatron FSDP'.
---

# Megatron FSDP Skill

For stable background and recommendation level, see:

- @docs/training/megatron-fsdp.md
- @skills/nemo-mbridge-perf-megatron-fsdp/card.yaml

## Enablement

Minimal Megatron FSDP override in Bridge:

```python
cfg.dist.use_megatron_fsdp = True
cfg.ddp.use_megatron_fsdp = True
cfg.ddp.data_parallel_sharding_strategy = "optim_grads_params"
cfg.ddp.average_in_collective = False
cfg.checkpoint.ckpt_format = "fsdp_dtensor"
```

Example recipe fixup:

```python
cfg = llama3_8b_pretrain_config()
cfg.dist.use_megatron_fsdp = True
cfg.ddp.use_megatron_fsdp = True
cfg.ddp.data_parallel_sharding_strategy = "optim_grads_params"
cfg.ddp.average_in_collective = False
cfg.checkpoint.ckpt_format = "fsdp_dtensor"
cfg.checkpoint.save = "/tmp/fsdp_ckpts"
cfg.checkpoint.load = None
```

Performance harness note:

```bash
python scripts/performance/launch.py --use_megatron_fsdp true
```

## Code Anchors

Bridge config definition:

```148:154:src/megatron/bridge/training/config.py
use_megatron_fsdp: bool = False
"""Use Megatron's Fully Sharded Data Parallel. Cannot be used together with use_torch_fsdp2."""

use_torch_fsdp2: bool = False
"""Use the torch FSDP2 implementation. FSDP2 is not currently working with Pipeline Parallel.
It is still not in a stable release stage, and may therefore contain bugs or other
potential issues."""
```

Bridge validation:

```1533:1578:src/megatron/bridge/training/config.py
if self.dist.use_megatron_fsdp and self.dist.use_torch_fsdp2:
    raise ValueError(...)
...
assert not self.dist.use_tp_pp_dp_mapping, "use_tp_pp_dp_mapping is not supported with Megatron FSDP"
...
assert self.checkpoint.ckpt_format == "fsdp_dtensor", (
    "Megatron FSDP only supports fsdp_dtensor checkpoint format"
)
```

Runtime wrapper selection:

```217:243:src/megatron/bridge/models/common/unimodal.py
if use_megatron_fsdp:
    DP = FullyShardedDataParallel
elif use_torch_fsdp2:
    DP = TorchFullyShardedDataParallel
else:
    DP = DistributedDataParallel
...
DP(
    config=get_model_config(model_chunk),
    ddp_config=ddp_config,
    module=model_chunk,
    ...
    pg_collection=pg_collection,
)
```

Perf harness overrides:
````
END THIRD-PARTY FILE 386972385200cd55

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First 2599 of 3892 bytes. © NVIDIA · Apache-2.0 · https://github.com/NVIDIA/skills/tree/HEAD/skills/nemo-mbridge-perf-megatron-fsdp/SKILL.md

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