gpu-architecture-fundamentals
gpu-architecture-fundamentals is an MLOps & model serving skill for AI agents, published by AMD-AGI in the Apex repository on GitHub. Skillspace rates gpu-architecture-fundamentals D (65/100) and it passed the safety scan; the rating is based on static analysis only.
This skill should be used when reasoning about GPU architecture fundamentals to guide kernel optimization choices such as memory hierarchy usage, execution model mapping, block sizing, and latency-aware tuning across HIP, Triton, and PyTorch.
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 71
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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