This half-day workshop provides an accelerated introduction to High-Performance Computing (HPC) through hands-on exercises in Linux, parallel programming with MPI, and AI-enabled scientific data analysis. Participants will learn the fundamentals of using an HPC system before applying these skills to analyze real-world power outage data from the U.S. Department of Energy’s EAGLE-I system. Using parallel data processing, visualization, and K-means clustering, attendees will discover how HPC enables scalable machine learning and data analytics while gaining practical experience solving a real scientific problem. This streamlined workshop is ideal for participants seeking a fast-paced introduction to HPC and its role in modern AI workflows.
Presented by Lawrence Livermore National Laboratory and Oak Ridge National Laboratory
Audience: Undergraduate students, graduate students, faculty, and researchers interested in learning the fundamentals of HPC and its applications to scientific computing and data analytics. No prior HPC experience is required, although basic programming experience is recommended.
Requirements: Participants must bring a fully charged laptop with Wi-Fi connectivity, a terminal capable of running ssh, and a government-issued photo ID to obtain access to workshop computing resources. Accounts providing access to the workshop HPC cluster will be supplied for all hands-on exercises.
🕐 8:00 AM–12:00 PM👤 All