Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms

Fuente: arXiv
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Autori principali: Zhang, Benran, Weinberg, Daniel, Hsu, Chih-En, Altman, Aaron R., Shi, Yuming, White III, James B., Vigil-Fowler, Derek, Louie, Steven G., Deslippe, Jack R., da Jornada, Felipe H., Li, Zhenglu, Del Ben, Mauro
Natura: Preprint
Pubblicazione: 2025
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author Zhang, Benran
Weinberg, Daniel
Hsu, Chih-En
Altman, Aaron R.
Shi, Yuming
White III, James B.
Vigil-Fowler, Derek
Louie, Steven G.
Deslippe, Jack R.
da Jornada, Felipe H.
Li, Zhenglu
Del Ben, Mauro
author_facet Zhang, Benran
Weinberg, Daniel
Hsu, Chih-En
Altman, Aaron R.
Shi, Yuming
White III, James B.
Vigil-Fowler, Derek
Louie, Steven G.
Deslippe, Jack R.
da Jornada, Felipe H.
Li, Zhenglu
Del Ben, Mauro
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2509_23018
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms
Zhang, Benran
Weinberg, Daniel
Hsu, Chih-En
Altman, Aaron R.
Shi, Yuming
White III, James B.
Vigil-Fowler, Derek
Louie, Steven G.
Deslippe, Jack R.
da Jornada, Felipe H.
Li, Zhenglu
Del Ben, Mauro
Materials Science
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.
title Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms
topic Materials Science
url https://arxiv.org/abs/2509.23018