cuda-tutor-setup
Skill4 starsChanged 9 months agoNo licenceView on GitHub
Generate an Obsidian-format CUDA StudyVault for learning NVIDIA's GPU programming stack. Three modes: (1) Curriculum mode (default, no source files needed) builds a prereq-ordered vault around the 6-topic learning path: CUDA kernels (threads/blocks/warps, memory hierarchy, TMA, WGMMA, cp.async), CUTLASS + CuTe (Layout/Tensor, MMA atoms, GEMM pipelines), cuTile (Python tile DSL), open-gpu-kernel-modules (RM, GSP firmware, UVM, kernel-open), NCCL (collectives, NVLink-SHARP, transports), and NVSHMEM (PGAS, symmetric heap, IBGDA); (2) Codebase mode generates an onboarding vault from a real CUDA/CUTLASS/NCCL/NVSHMEM/driver source tree; (3) Document mode turns NVIDIA whitepapers, GTC slide decks, and PDFs into study notes. Mode is auto-detected from CWD markers. Use when the user wants to learn CUDA from scratch, onboard onto a GPU codebase, build an exercise list for CUDA topics, or preprocess NVIDIA PDFs/docs into structured study material. Pair with the `cuda-tutor` skill to quiz against the resulting vault.
In this repository31 other files it gives its agents.
- skills/auto-gpu-kernel/references/agents.mdAGENTS.md
- academic-grant-proposalSkill
- academic-rebuttalSkill
- academic-reviewerSkill
- academic-writingSkill
- ast-grepSkill
- auto-gpu-kernelSkill
- better-grepSkill
- citation-convertSkill
- conference-plotSkill
- cuda-tutorSkill
- education-statementSkill
- add-cuda-kernelSkill
- benchmark-kernelSkill
- debug-cuda-crashSkill
- function-dep-searchSkill
- cuda-kernelsSkill
- meeting-summarySkill
- mem0Skill
- openvikingSkill
- research-statementSkill
- add-jit-kernelSkill
- add-sgl-kernelSkill
- ci-workflow-guideSkill
- debug-cuda-crashSkill
- generate-profileSkill
- sglang-bisect-ci-regressionSkill
- write-sglang-testSkill
- triton-tutor-setupSkill
- triton-tutorSkill
- tutor-handoutsSkill
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