Grain Growth and Array Programming - Modeling Techniques for Materials Science

Grain Growth and Array Programming - Modeling Techniques for Materials Science

Explore grain growth modeling and array programming techniques in this 18-minute conference talk from Dyalog '23. Discover how materials science students can benefit from using array programming and APL to solve computational problems. Follow the journey from a simple Python implementation to more advanced solutions using NumPy and APL. Learn about the challenges of modeling grain growth, including addressing unrealistic patterns and singular grain cases. Compare the performance of different programming approaches through benchmarks, and gain insights into embedding APL with Py'n'APL. Understand the practical applications of array programming in materials science and the potential advantages of using APL for computational tasks.