#exascale-computing News & Analysis

Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data

Researchers have developed an exascale workflow using graph foundation models trained on 544+ million atomistic structures to accelerate materials discovery. The system can screen 1.1 billion structures in 50 seconds—a task requiring years of traditional computation—and demonstrates strong transfer learning capabilities across diverse chemical applications.