cpp-loop-optimization
Skill0 starsChanged 5 months agoNo licenceView on GitHub
A catalog and decision guide for optimizing hot C and C++ loops — SIMD/vectorization, cache locality, tiling/blocking, and the full family of loop transformations (fusion, fission, unrolling, interchange, peeling, strip-mining, sentinel, skewing, and more). Use this skill whenever the user is making a numeric or data-processing loop faster, mentions a loop showing up in a CPU profile, asks about vectorization, `__restrict__`, cache misses, matrix-multiply or stencil performance, low-latency code (trading/audio/game loops), or wants to know which loop transformation applies — even if they just say "this loop is slow" or "speed this up" without naming a technique. Also trigger for nested-loop memory-access problems, AoS-vs-SoA layout questions, and reading or fixing why the compiler "won't vectorize.
In this repository6 other files it gives its agents.
- camb-devSkill
- cosmolike-devSkill
- docker-mlSkill
- explaining-codeSkill
- porting-legacy-physics-codeSkill
- pytorch-teaching-notebook-styleSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.