# Palmetto Gpu Usage Advisor

> Inspect Palmetto GPU usage and recommend which card type and GPU count to request right now. Use when the user asks about current GPU occupancy, cluster card availability, or which GPU type/count is the best choice before submitting a Palmetto job.

- Skill: `kwongfuk/palmetto-gpu-usage-advisor` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add kwongfuk/palmetto-gpu-usage-advisor`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kwongfuk/palmetto-gpu-usage-advisor/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: KwongFuk (https://skillmd.com/u/kwongfuk)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/kwongfuk/palmetto-gpu-usage-advisor

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# Palmetto GPU Usage Advisor

Use this skill when the user wants a current Palmetto GPU view and a plain recommendation such as:
- which card type is least congested now
- whether 1, 2, 4, or 8 GPUs are realistic right now
- which nodes currently have the most free GPUs
- whether H100, H200, or A100 is the best current target

## Workflow

1. Run the usage inspector:

```bash
python /home/gguo/.codex/skills/palmetto-gpu-usage-advisor/scripts/inspect_gpu_usage.py
```

2. Read the output in two layers:
- per-GPU-type usage summary
- final `Current card suggestions` section

3. Explain the result in user terms:
- cluster-wide usage by card type
- whether the cluster is fragmented or has idle nodes
- what to request now for `1`, `2`, `4`, or `8` GPU jobs

## Output Interpretation

- `idle`: at least one node of that GPU type is completely free
- `mixed`: nodes exist with some GPUs free, but those nodes are fragmented
- `full`: no GPUs free on those nodes
- `max_free_on_one_node`: the largest single-node GPU block currently visible for that card type

## Decision Guidance

- Prefer card types with more idle nodes for new training jobs.
- Prefer card types with larger `max_free_on_one_node` for multi-GPU single-node jobs.
- For `4` or `8` GPU jobs, treat fragmentation as a real blocker even if total free GPUs across the cluster look high.
- If the user needs an exact job-fit decision for a specific `sbatch` script, switch to `$palmetto-slurm-fit-check`.

## Notes

- The inspector handles the local `scontrol` shared-library issue automatically.
- The summary is partition-specific and defaults to `work1`.
- This skill gives a current cluster recommendation, not a guaranteed start time.