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Gpu Sharing Advisor

skill

- Decide between MIG, MPS, and time-slicing for sharing NVIDIA GPUs across Kubernetes workloads, and produce the config to implement the choice. Use whenever the user asks about GPU sharing, fractional GPUs, partitioning a GPU, MIG profiles, Multi-Process Service, time-slicing, GPU oversubscription, virtual GPUs, "our GPUs sit idle", low GPU utilization, running many small models on one GPU, packing inference replicas, or letting multiple researchers or notebooks share an A100/H100/H200/L4. Also use when reviewing a time-slicing ConfigMap, a MIG strategy (single vs mixed), or nvidia.com/mig- resource requests. …

Works with: Claude Code (native)  ·  Cursor, Codex CLI (manual)
native: this artifact type is that client's own format

Install (Claude Code):

cp -r gpu-sharing-advisor ~/.claude/skills/

Security audit

Not scanned yet. We audit npm-published capabilities for known advisories, install-time scripts and permission surface; this one has no npm package we can resolve, or has not reached the queue.

Its own instructions

Its SKILL.md says when to use it, shows worked examples and states a limitation.

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source ↗  ·  skill:Cloud-Byte-Consulting/gpu-sharing-advisor

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Measured 2026-08-22  ·  scorer s5  ·  how  ·  something wrong here?