Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
Star History
Momentum
+50
STARS · LAST 30 DAYS
2
PER DAY
#253
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +14 | +50 | +180 |
| Per day | 2 | 2 | 2 |
| Forks gained | +1 | +6 | +14 |
ai-performance-engineering gained 50 stars in the last 30 days, about 2 a day, and now has 2K. It is about 1 year old and has averaged roughly 2K stars a year. It ranks #253 among Python repositories and #1,878 across all languages on GitHubRepo.
Trending Record
3
DAYS ON TRENDING
#1720
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ai-performance-engineering has maintained a continuous presence across global trending indexes, peaking at #1720. Below is the 30-day activity profile:
💡 Overview
ai-performance-engineering is an open-source project written in Python: Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install ai-performance-engineering⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ai-performance-engineering coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed ai-performance-engineering into Python backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install ai-performance-engineering using your package manager: `pip install ai-performance-engineering`
Initialize your project workspace or configuration file for ai-performance-engineering.
Import ai-performance-engineering into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ai-performance-engineering --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
cfregly/ai-performance-engineering is currently ranked #1,878 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #1,873 | matrixorigin/matrixone | Go | ★ 2K | Compare ↗ |
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| #1,877 | numtide/llm-agents.nix | Nix | ★ 2K | Compare ↗ |
| #1,878 | cfregly/ai-performance-engineering This Project | Python | ★ 2K | |
| #1,878 | lsegal/yard | Ruby | ★ 2K | Compare ↗ |
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Frequently Asked Questions
What does ai-performance-engineering do? +
Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
What language is ai-performance-engineering written in? +
The primary language is Python. Topics include: software.
Is ai-performance-engineering actively maintained? +
Yes, the last recorded push was on Sep 26, 2026 with 3 open issues being tracked.
How many stars does ai-performance-engineering have? +
ai-performance-engineering has 2,010 stars and 275 forks on GitHub.
How does ai-performance-engineering rank among GitHub repositories? +
With 2,010 stars, cfregly/ai-performance-engineering is ranked #1,878 globally across all repositories tracked on GitHubRepo and #253 among Python projects.
What license is ai-performance-engineering distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
