plainsight-systems

plainsight-systems / cpp-perf-guidelines

Public

Low-level C++ performance guidelines for game-engine and embedded systems — the technique layer below the ISO C++ Core Guidelines

10
3
85% credibility
Found May 25, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This is a curated library of low-level C++ performance guidelines designed for game engine and embedded systems developers. It contains 64 guidelines organized into 8 categories covering topics like memory management, data layout optimization, object lifetime, and SIMD vectorization. The corpus provides concrete, technique-level guidance that goes beyond general programming advice—instead of just saying 'minimize allocations,' it shows you exactly how to implement arena allocators and custom memory pools. Developers can browse the guidelines directly or access them through an automated server that lets AI assistants search and retrieve relevant techniques. The project is well-documented with clear formatting rules and includes a validation tool to ensure consistency.

How It Works

1
🔍 You discover you need faster code

You're building a game engine or embedded system and realize you need to squeeze out more performance from your C++ code.

2
📚 You find a collection of proven techniques

You stumble upon a curated library of low-level performance guidelines written specifically for developers like you.

3
You choose your path
📂
Browse by topic

You explore categories like memory management, data layout, or SIMD optimization to find what matters most.

🔎
Search directly

You type in what you're looking for and instantly find matching guidelines.

4
📖 You read a guideline

Each guideline explains why it matters, what to do, shows examples, and warns about tradeoffs.

5
💡 You apply the technique

You take the concrete advice and implement it in your own code, knowing it's been reviewed by experts.

🚀 Your code runs faster

You've successfully applied a proven technique and your game engine or embedded system performs better.

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Star Growth

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AI-Generated Review

What is cpp-perf-guidelines?

A curated knowledge base of low-level C++ performance guidelines targeting game-engine and embedded-systems developers. Where the ISO C++ Core Guidelines stop at "use the standard library well," this corpus owns the concrete techniques underneath: custom allocators, cache-aware data layouts, copy/move discipline, SIMD vectorization, and embedded constraints. The corpus comes with a Python-based validator and an MCP server integration, letting AI agents query guidelines by category, ID, or semantic search.

Why is it gaining traction?

Game and embedded developers constantly bump against the gap between abstract performance advice and actionable implementation. This repo fills that gap with technique-level guidance written for real constraints: WCET budgets, cache-line ping-pong, and avoiding heap allocation in hot paths. The eight-category taxonomy (memory, copy-move, cache-layout, lifetime, embedded, concurrency, codegen, SIMD) provides a coherent mental model for low-level C++ optimization. MCP server integration signals it's built for AI-assisted development pipelines.

Who should use this?

Game engine programmers optimizing frame budgets, embedded systems engineers working without exceptions or dynamic allocation, and C++ developers preparing for low-level interview questions. Also useful for AI agents that need structured, machine-readable C++ performance knowledge.

Verdict

Early-stage but promising. At 10 stars with all guidelines in draft status, this is a foundation rather than a finished product. The 0.85% credibility score reflects solid organizational structure and clear versioning discipline, but contributors should validate locally before relying on content in production pipelines. Watch this for growth; do not depend on it yet.

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