- Preparation Day (virtual): Tuesday, June 16, 2026 from 9 am - 11 am (Pacific Time)
- Summer Institute (in-person): Tuesday, June 23 - Thursday, June 25, 2026 from 8 am - 5:30 pm (Pacific Time)
Application closes Wednesday, April 8, 2026.
The San Diego Supercomputer Center (SDSC) Cyberinfrastructure-Enabled Machine Learning (CIML) is focused on teaching researchers and students the best practices for effectively running artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications on advanced cyberinfrastructure (CI) and high-performance computing (HPC) systems. The National Artificial Intelligence Research Resource (NAIRR) pilot is an NSF-led initiative designed to democratize access to AI research by providing U.S. researchers and educators with crucial infrastructure, including computational power, datasets, and training tools.
The CIML Summer Institute introduces artificial intelligence, machine learning, deep learning (AI/ML/DL) and LLM concepts to researchers, developers and educators. We will introduce techniques and methods needed to migrate their AI applications from smaller, locally run resources, such as laptops and workstations, to large-scale HPC systems, such as the SDSC’s Expanse supercomputer. Participants will have the opportunity to accelerate their learning process through highly interactive classes with hands-on tutorials using SDSC’s Expanse.
In addition, the CIML SI broadens participation in AI/ML/DL research by actively recruiting participants from institutions across the United States that have limited or no access to advanced supercomputing or CI resources. This effort will expand the reach of advanced computational infrastructure and build capacity at institutions of all types and sizes. We will balance attendees across multiple scientific disciplines and institutional settings to develop a robust national AI research community, ensuring that advanced cyberinfrastructure training and expertise extend beyond traditional research-intensive institutions.
Additionally, attendees will have opportunities to meet one-on-one with SDSC’s experts to discuss in detail the best techniques to solve their specific AI problems.
Prerequisite
- Knowledge or experience with machine learning and AI is required
- Familiarity with UNIX/Linux shell
- Basic programming skills (especially Python) are strongly recommended
- Interest in AI application
Program includes
- Overview of High-Performance Computing (HPC) and Parallel Computing Concepts
- Instructional and hands-on exercises focused on HPC techniques, Machine Learning, Scalable Machine Learning, Deep Learning, and Large Language Model (LLM) inference
- Team works on prepared training problems