Work

Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research

Year: 2023

Type: conference-paper

Abstract: Today, machine learning is being deployed for use in practice across all fields of science, engineering, and medicine. Although there are many educational resources on machine learning, they focus on executing workflows at modest scale. Our training program, Cyberinfrastructure-Enabled Machine Learning (CIML), focuses on the core competencies for at-scale ML workflows, and integrates topics from high-performance computing, data management, advanced cyberinfrastructure, reproducible computing, calable machine learning, and deep learning. The CIML project hosts an annual workshop that brings together researchers and practitioners from all fields, where the training program focuses on teaching participants the basics of high-performance computing (HPC) and ML at scale. Adopting "Findable, Accessible, Interoperable, and Reusable" (FAIR) practices, all CIML training material is made freely available online via GitHub. We describe the CIML project and its training program, report on its impact to date, and discuss our future plans for the project.

Source: Practice and Experience in Advanced Research Computing

DOI: 10.1145/3569951.3597543