OSG_NAIRR2026

NAIRR 2026 Annual Meeting Tutorial Title: Training Ensembles Across NAIRR Resources Ian Ross, University of Wisconsin–Madison Danny Morales, University of Wisconsin–Madison Modern AI research requires training ensembles of models: hyperparameter optimization explores multiple configurations, cross-validation needs models trained on different data splits, and multiple models can be combined for better predictions. The traditional approach of training an ensemble of models sequentially is time-consuming and lengthens the time-to-insight. This tutorial demonstrates a throughput oriented approach: plan once, then distribute your ensemble training across all available resources simultaneously. This hands-on tutorial teaches you how to leverage services provided by the Partnership to Advance Throughput Computing (PATh) to train ensembles of machine learning models across the NAIRR resources. After planning and running the first training, scaling to dozens of models requires minimal additional effort. https://events.internet2.edu/website/89730/tutorials/