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Publications of SPCL

N. Vetsch, A. Maeder, V. Maillou, A. Winka, J. Cao, G. Kwasniewski, L. Deuschle, T. Hoefler, A. Nikolaos Ziogas, M. Luisier:
	Ab-initio Quantum Transport with the GW Approximation, 42,240 Atoms, and Sustained Exascale Performance (In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'25), presented in St. Louis, MO, USA, Nov. 2025) Abstract Designing nanoscale electronic devices such as the currently manufactured nanoribbon field-effect transistors (NRFETs) requires advanced modeling tools capturing all relevant quantum mechanical effects. State-of-the-art approaches combine the non-equilibrium Green's function (NEGF) formalism and density functional theory (DFT). However, as device dimensions do not exceed a few nanometers anymore, electrons are confined in ultra-small volumes, giving rise to strong electron-electron interactions. To account for these critical effects, DFT+NEGF solvers should be extended with the GW approximation, which massively increases their computational intensity. Here, we present the first implementation of the NEGF+GW scheme capable of handling NRFET geometries with dimensions comparable to experiments. This package, called QuaTrEx, makes use of a novel spatial domain decomposition scheme, can treat devices made of up to 84,480 atoms, scales very well on the Alps and Frontier supercomputers (>80% weak scaling efficiency), and sustains an exascale FP64 performance on 42,240 atoms (1.15 Eflop/s). Documents download article: access preprint on arxiv:
	BibTeX
@inproceedings{2025_abinitio_gb,   author={Nicolas Vetsch and Alexander Maeder and Vincent Maillou and Anders Winka and Jiang Cao and Grzegorz Kwasniewski and Leonard Deuschle and Torsten Hoefler and Alexandros Nikolaos Ziogas and Mathieu Luisier},   title={{Ab-initio Quantum Transport with the GW Approximation, 42,240 Atoms, and Sustained Exascale Performance}},   year={2025},   month={11},   booktitle={Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'25)},   location={St. Louis, MO, USA},   doi={https://doi.org/10.1145/3712285.3771784}, }