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With the increasing prevalence of artificial intelligence (AI) in diversescience/engineering communities, AI models emerge on an unprecedented scaleamong various domains. However, given the complexity and diversity of thesoftware and hardware environments, reusing AI artifacts (models and datasets)is extremely challenging, especially with AI-driven science applications.Building an ecosystem to run and reuse AI applications/datasets at scaleefficiently becomes increasingly essential for diverse science and engineeringand high-performance computing (HPC) communities. In this paper, we innovateover an HPC-AI ecosystem -- HPCFair, which enables the Findable, Accessible,Interoperable, and Reproducible (FAIR) principles. HPCFair enables thecollection of AI models/datasets allowing users to download/upload AI artifactswith authentications. Most importantly, our proposed framework providesuser-friendly APIs for users to easily run inference jobs and customize AIartifacts to their tasks as needed. Our results show that, with HPCFair API,users irrespective of technical expertise in AI, can easily leverage AIartifacts to their tasks with minimal effort.

Towards Seamless Management of AI Models in High-Performance Computing