Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

Teranishi, Keita, Menon, Harshitha, Godoy, William F., Balaprakash, Prasanna, Bau, David, Ben-Nun, Tal, Bhatele, Abhinav, Franchetti, Franz, Franusich, Michael, Gamblin, Todd, Georgakoudis, Giorgis, Goldstein, Tom, Guha, Arjun, Hahn, Steven, Iancu, Costin, Jin, Zheming, Jones, Terry, Low, Tze Meng, Mankad, Het, Miniskar, Narasinga Rao, Monil, Mohammad Alaul Haque, Nichols, Daniel, Parasyris, Konstantinos, Pophale, Swaroop, Valero-Lara, Pedro, Vetter, Jeffrey S., Williams, Samuel, Young, Aaron

–arXiv.org Artificial Intelligence 

We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challenges associated with leveraging state-of-the-art AI technologies to develop such a unique and niche class of software and outline our research directions in the two US Department of Energy--funded projects for advancing HPC Software via AI: Ellora and Durban.

arXiv.org Artificial Intelligence

Nov-27-2025

arXiv.org    PDF

Add feedback