TY - GEN
T1 - Multiscale Light-Matter Dynamics in Quantum Materials
T2 - 2025 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025
AU - Razakh, Taufeq Mohammed
AU - Linker, Thomas
AU - Luo, Ye
AU - Piroozan, Nariman
AU - Pennycook, John
AU - Kumar, Nalini
AU - Musaelian, Albert
AU - Johansson, Anders
AU - Kozinsky, Boris
AU - Kalia, Rajiv K.
AU - Vashishta, Priya
AU - Shimojo, Fuyuki
AU - Hattori, Shinnosuke
AU - Nomura, Ken Ichi
AU - Nakano, Aiichiro
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/11/15
Y1 - 2025/11/15
N2 - Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electrons, and atoms over vast spatiotemporal scales on Exaflop/s computers with increased heterogeneity and low-precision focus. We present a paradigm shift that solves the multiscale/multiphysics/heterogeneity challenge harnessing hardware heterogeneity and low-precision arithmetic. Divide-conquer-recombine algorithms divide the problem into not only spatial but also physical subproblems of small dynamic ranges and minimal mutual information, which are mapped onto best-characteristics-matching hardware units, while metamodel-space algebra minimizes communication and precision requirements. Using 60,000 GPUs of Aurora, DC-MESH (divide-and-conquer Maxwell-Ehrenfest-surface hopping) and XS-NNQMD (excited-state neural-network quantum molecular dynamics) modules of MLMD (multiscale light-matter dynamics) software were 152- and 3,780-times faster than the state-of-the-art for 15.4 million-electron and 1.23 trillion-atom PbTiO3 material, achieving 1.87 EFLOP/s for the former. This enabled the first study of light-induced switching of topological superlattices for future ferroelectric 'topotronics'.
AB - Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electrons, and atoms over vast spatiotemporal scales on Exaflop/s computers with increased heterogeneity and low-precision focus. We present a paradigm shift that solves the multiscale/multiphysics/heterogeneity challenge harnessing hardware heterogeneity and low-precision arithmetic. Divide-conquer-recombine algorithms divide the problem into not only spatial but also physical subproblems of small dynamic ranges and minimal mutual information, which are mapped onto best-characteristics-matching hardware units, while metamodel-space algebra minimizes communication and precision requirements. Using 60,000 GPUs of Aurora, DC-MESH (divide-and-conquer Maxwell-Ehrenfest-surface hopping) and XS-NNQMD (excited-state neural-network quantum molecular dynamics) modules of MLMD (multiscale light-matter dynamics) software were 152- and 3,780-times faster than the state-of-the-art for 15.4 million-electron and 1.23 trillion-atom PbTiO3 material, achieving 1.87 EFLOP/s for the former. This enabled the first study of light-induced switching of topological superlattices for future ferroelectric 'topotronics'.
KW - molecular dynamics
KW - Multiscale light-matter dynamics
KW - neural network
KW - quantum dynamics
KW - topotronics
UR - https://www.scopus.com/pages/publications/105023972151
U2 - 10.1145/3712285.3771785
DO - 10.1145/3712285.3771785
M3 - Conference contribution
AN - SCOPUS:105023972151
T3 - Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025
SP - 36
EP - 47
BT - Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2025
PB - Association for Computing Machinery, Inc
Y2 - 16 November 2025 through 21 November 2025
ER -