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Artificial intelligence (AI) applications are increasingly prevalent in various aspects of our daily lives. One such application is ChatGPT, which has garnered significant interest from professionals across different fields seeking to leverage AI for diverse purposes, in- cluding parallel programming. However, concerns have been raised regarding ChatGPT’s ability to generate correct and efficient code. The objective of this study is to evaluate the effectiveness of ChatGPT (GPT-3.5), an advanced language model, for parallel programming using OpenACC. Parallel pro- gramming plays a crucial role in accelerating computationally intensive applications and improving overall performance. OpenACC, a parallel programming standard, enables de- velopers to harness the computational power of GPUs for application acceleration. By conducting a series of experiments, we compare different approaches to parallel programming, with and without the assistance of ChatGPT. Key evaluation factors include execution performance, code quality, and user-friendliness. The results suggest that integrating ChatGPT can positively impact the parallel pro- gramming process. However, limitations and challenges are identified, such as the need for proper parameter adjustment and reliance on training data utilized by ChatGPT. Sugges- tions for future research directions are provided to address the identified limitations and further enhance the integration of ChatGPT into the parallel programming workflow.
Costa et al. (Thu,) studied this question.