"Design DeepSpeed pipeline parallelism, MoE layers, sequence
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill parallelism-moe --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Parallelism Moe?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-parallelism-moe)More formats (shields.io, HTML) on the badges page.
---
name: parallelism-moe
description: "Design DeepSpeed pipeline parallelism, MoE layers, sequence
parallelism, AutoSP, and activation checkpointing for training workflows."
disable-model-invocation: true
metadata:
disco-role: operating
license: Apache 2.0
---
# Parallelism, MoE, and Checkpointing
Use this sub-skill when a task involves DeepSpeed training parallelism beyond basic ZeRO: pipeline parallel models, MoE layers, expert tensor parallelism, Ulysses or HF sequence parallelism, AutoSP, or activation checkpointing.
## Route by Task
- **Pipeline parallelism**: use `references/workflows.md#pipeline-parallelism` for `PipelineModule`, `LayerSpec`, `TiedLayerSpec`, `ProcessTopology`, and `PipelineEngine.train_batch()` / `eval_batch()` loops.
- **MoE and expert parallelism**: use `references/workflows.md#moe-and-expert-parallelism` for `deepspeed.moe.layer.MoE`, expert-parallel sizing, optimizer param groups, tuple outputs, PR-MoE, and expert tensor parallelism.
- **Sequence parallelism**: use `references/workflows.md#sequence-parallelism` for `DistributedAttention`, Ulysses HF registration, dataloader sharding, loss aggregation, and AutoSP.
- **Activation checkpointing**: use `references/workflows.md#activation-checkpointing` for `deepspeed.checkpointing.configure()` and checkpoint placement with model/pipeline parallelism.
- **API signatures**: run `scripts/inspect_parallelism_api.py --help`, then use it to print import availability and signatures without launching distributed jobs.
## Boundaries
- Stay here for `PipelineModule`, `LayerSpec`, `TiedLayerSpec`, `ProcessTopology`, `PipelineEngine`, MoE layers, MoE optimizer groups, sequence-parallel APIs, AutoSP, and activation checkpointing.
- Use the training-configuration sub-skill for basic ZeRO configuration, optimizer/offload tuning not specific to MoE, and standard `deepspeed.initialize()` config assembly.
- Use the inference/injection sub-skill for inference tensor parallelism and kernel injection.
- Use ops/tooling guidance for extension builds, fused op installation, NVMe, or environment build failures.
## References
- `references/api-reference.md` lists the installed signatures and source-backed API responsibilities.
- `references/workflows.md` gives compact design workflows and minimal patterns.
- `references/troubleshooting.md` maps common parallelism failures to likely fixes.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!