- By:
- Zhang, Benran; Weinberg, Daniel; Hsu, Chih-En; Altman, Aaron; Shi, Yuming; White, James ; Vigil-Fowler, Derek; Louie, Steven; Deslippe, Jack; da Jornada, Felipe; Li, Zhenglu; Del Ben, Mauro
- Page Number:
- 48-59
- Book Title:
- SC '25: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
- Publication Date:
- January 14, 2026
- Publisher Location:
- Association for Computing Machinery (ACM), New York, New York, United States of America
- Conference Name:
- International Conference for High Performance Computing, Networking, Storage and Analysis (SC '25)
- Conference Location:
- St. Louis, Missouri, United States of America
- Conference Sponsor:
- Association for Computing Machinery (ACM)
- View DOI Listing:
- https://doi.org/10.1145/3712285.3772093
Abstract
Advanced ab initio materials simulations face growing challenges as increasing systems and phenomena complexity requires higher accuracy, driving up computational demands. Quantum many-body GW methods are state-of-the-art for treating electronic excited states and couplings but often hindered due to the costly numerical complexity. Here, we present innovative implementations of advanced GW methods within the BerkeleyGW package, enabling large-scale simulations on Frontier and Aurora exascale platforms. Our approach demonstrates exceptional versatility for complex heterogeneous systems with up to 17,574 atoms, along with achieving true performance portability across GPU architectures. We demonstrate excellent strong and weak scaling to thousands of nodes, reaching double-precision core-kernel performance of 1.069 ExaFLOP/s on Frontier (9,408 nodes) and 707.52 PetaFLOP/s on Aurora (9,600 nodes), corresponding to 59.45% and 48.79% of peak, respectively. Our work demonstrates a breakthrough in utilizing exascale computing for quantum materials simulations, delivering unprecedented predictive capabilities for rational designs of future quantum technologies.
