This tutorial focuses on the computational aspects of training and deploying large-scale AI models using high-performance computing (HPC). Topics include distributed training, multi-GPU and multi-node acceleration, mixed-precision optimization, efficient data handling, and resource management on supercomputing clusters. Special attention is given to transformer-based architectures, self- and semi-supervised learning, and energy-efficient AI practices. Participants will gain […]

This tutorial highlights two essential frameworks for developing robust, multi-step agents: LangGraph and the Model Context Protocol (MCP). For additional resources, please refer to the companion repository.