mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
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a680d0472b
Adds a Claude Code plugin structure that exposes each NVIDIA DGX Spark
playbook as a triggerable skill, with an index skill ('dgx-spark') that
routes users to the right leaf based on intent and encodes the
relationship graph between playbooks (prerequisites, alternatives,
composes-with, upgrade paths).
Structure:
- overrides/*.md hand-curated frontmatter + Related sections
- scripts/generate.mjs zero-dep Node generator: nvidia + overrides → skills
- scripts/install.sh symlinks skills into ~/.claude/skills (--plugin mode available)
- skills/ committed, browsable, installable without Node
- .github/workflows/ auto-regenerates skills/ when playbooks/overrides change
Initial curated leaves: ollama, open-webui, vllm, connect-to-your-spark.
Remaining 37 leaves use generator fallback (title + tagline + summary
extracted from README) and can be curated incrementally via overrides/.
26 lines
1.1 KiB
Markdown
26 lines
1.1 KiB
Markdown
---
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name: dgx-spark-jax
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description: Optimize JAX to run on Spark — on NVIDIA DGX Spark. Use when setting up jax on Spark hardware.
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---
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<!-- GENERATED:BEGIN from nvidia/jax/README.md -->
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# Optimized JAX
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> Optimize JAX to run on Spark
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JAX lets you write **NumPy-style Python code** and run it fast on GPUs without writing CUDA. It does this by:
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- **NumPy on accelerators**: Use `jax.numpy` just like NumPy, but arrays live on the GPU.
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- **Function transformations**:
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- `jit` → Compiles your function into fast GPU code
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- `grad` → Gives you automatic differentiation
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- `vmap` → Vectorizes your function across batches
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- `pmap` → Runs across multiple GPUs in parallel
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**Outcome**: You'll set up a JAX development environment on NVIDIA Spark with Blackwell architecture that enables
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high-performance machine learning prototyping using familiar NumPy-like abstractions, complete with
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GPU acceleration and performance optimization capabilities.
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**Full playbook**: `/Users/jkneen/Documents/GitHub/dgx-spark-playbooks/nvidia/jax/README.md`
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<!-- GENERATED:END -->
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