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Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Wenhua Yang, Chong Zhang, Minxue Pan
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, (ESEC/FSE’23), 2023

@inproceedings{yang2023understanding,

   title={Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts},

   author={Yang, Wenhua and Zhang, Chong and Pan, Minxue},

   booktitle={Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering},

   pages={1444–1456},

   year={2023}

}

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GPUs have cemented their position in computer systems, not restricted to graphics but also extensively used for general-purpose computing. With this comes a rapidly expanding population of developers using GPUs for programming. However, programming with GPUs is notoriously difficult due to their unique architecture and constant evolution. A large number of developers have encountered problems of one kind or another, and many of them have turned to Q&A sites for help. Unfortunately, there has been no prior work to comprehensively study the topics discussed and challenges encountered by developers in GPU programming. To fill this knowledge gap, we conduct a comprehensive study to understand the topics and challenges of GPU programming using Stack Overflow. We collect 25,269 relevant posts from Stack Overflow, propose a novel approach that combines automatic techniques and manual thematic analysis to extract topics, and build a taxonomy of topics with detailed discussions of the popularity, difficulty, and changing trends of these topics. In addition, we analyzed relevant posts through extensive manual efforts to understand the challenges of each topic and to summarize them for future research.
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