Parallel Code

Parallel code generation and optimization are active research areas aiming to automate the complex process of writing efficient parallel programs for high-performance computing. Current efforts leverage large language models (LLMs) and graph neural networks (GNNs) to translate between parallel programming languages, automatically parallelize sequential code, and optimize existing parallel code for various architectures. These advancements promise to significantly reduce the time and expertise required for developing high-performance parallel applications, accelerating scientific discovery and technological innovation across diverse fields.