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spark-memory-thermal-ops

Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour…

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What it does and how to use it

A skill that teaches Claude Code to do general tasks well. It is packaged knowledge the model uses whenever it is relevant.

  1. Install the skill (command above).
  2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
  3. No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/wshobson-agents__spark-memory-thermal-ops && curl -fsSL https://doutorai.pt/data/lib/skills__wshobson-agents__spark-memory-thermal-ops.md -o .claude/skills/wshobson-agents__spark-memory-thermal-ops/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

---
name: spark-memory-thermal-ops
description: Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.
---

# Spark Memory & Thermal Ops

DGX Spark's GB10 chip has one 128GB unified
memory (UMA) pool shared by CPU and GPU, and a
sustained power ceiling well below its rated
figure. Both break discrete-GPU assumptions:
headroom isn't what `nvidia-smi` reports, and a
run that starts fast will slow down mi

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