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K. Teranishi, H. Menon, W. F. Godoy, P. Balaprakash, D. Bau, T. Ben-Nun, A. Bathele, Franz Franchetti, M. Franusich, T. Gamblin, G. Georgakoudis, T. Goldstein, A. Guha, S. Hahn, C. Iancu, Z. Jin, T. Jones, Tze-Meng Low, H. Mankad, N. R. Miniskar, M. A. H. Monil, D. Nichols, K. Parasyris, S. Pophale, P. Valero-Lara, J. Vetter, S. Williams and A. Young (Proc. ISC High Performance, arXiv 2505.08135, 2025)
Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions
Comment: 1st International Workshop on Foundational Large Language Models Advances for HPC (LLM4HPC)
Published paper (link to publisher)
Bibtex

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.

Keywords:
AI, High performance computing (HPC), Software