fkl-implementing-data-parallel-patterns
fkl-implementing-data-parallel-patterns is a Design patterns & component architecture skill for AI agents, published by Libraries-Openly-Fused in the FusedKernelLibrary repository on GitHub. Skillspace rates fkl-implementing-data-parallel-patterns F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Implement a new Data Parallel Pattern (DPP) for the Fused Kernel Library. Covers the anatomy of a DPP struct, device-side invocation of IOps (the IOp-form table, reading inputs, fusing epilogues into the write), compile-time vs runtime types, vector types, and testing. Use when adding an algorithm to FKL that requires thread coordination, or when debugging a DPP's internal device execution.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 53
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.
Our review
- Architecture
- 99 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- High-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- dynamic code execution (eval/exec)
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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