An Introduction and Tutorial of the Beagle Framework

2026-07-07

AI Summary

This work addresses the computational inefficiency of traditional genetic programming when applied to large-scale populations in symbolic regression tasks. To overcome this limitation, the study introduces Beagle, a high-throughput parallel framework that systematically integrates GPU acceleration into genetic programming via CUDA. Beagle enables efficient evolution of large populations, significantly enhancing both search efficiency and scalability for symbolic regression. The framework is accompanied by comprehensive documentation and tutorials, offering researchers and practitioners a practical and powerful tool for tackling complex symbolic regression problems.

Abstract

The Beagle framework is a GPU-based genetic programming framework that enables highly efficient genetic programming search using large population sizes by leveraging NVIDIA GPUs. This technical guide provides an introduction to the Beagle framework and provides detailed instructions for using the framework for symbolic regression problems.

Problem

• genetic programming
• GPU acceleration
• symbolic regression
• large population
• Beagle framework

Innovation

• GPU-based genetic programming
• Beagle framework
• large population sizes
• symbolic regression
• high-performance computing