PerfRL combines small language models with reinforcement learning to automatically optimize code performance across diverse hardware and software environments.

• Addresses the challenge of manual code optimization in rapidly evolving tech landscapes
• Leverages small, efficient language models rather than large, resource-intensive ones
• Demonstrates the viability of AI-driven optimization without massive computational resources
• Provides a framework for automating tedious optimization tasks developers typically handle manually

This research advances engineering practices by creating more efficient software development workflows and potentially reducing the expertise barrier needed for code optimization across diverse platforms.

PerfRL: A Small Language Model Framework for Efficient Code Optimization