aie-kernel-opt
aie-kernel-opt is a Runtime diagnostics & profiling skill for AI agents, published by Xilinx in the mlir-aie repository on GitHub. Skillspace rates aie-kernel-opt D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Standalone guide to optimizing AIE / Peano-compiled kernels (INT8 conv, matmul, attention, elementwise). Covers the measure-first methodology (baseline, bit-exact gate, ablation, verify-in-.o) AND the catalog of concrete levers in priority order — loop hints, compile-time constants, killing __divsi3, branch-splitting, vectorized epilogue, operand-layout pre-pack, explicit wide packing, wider mmul, DMA layout offload — each with the constraints to respect and a measured delta.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 667
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
- 90 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.