Quasiparticle self-consistent many-body perturbation theory (MBPT) methods that update both eigenvalues and eigenvectors can calculate the excited-state properties of molecular systems without depending on the choice of starting points. However, those methods are computationally intensive even on modern multi-core central processing units (CPUs) and thus typically limited to small systems. Many-core accelerators such as graphics processing units (GPUs) may be able to boost the performance of those methods without losing accuracy, making starting-point-independent MBPT methods applicable to large systems. Here, we GPU accelerate MOLGW, a Gaussian-based MBPT code for molecules, with open accelerators (OpenACC) and achieve speedups of up to 9.7x over 32 open multi-processing (OpenMP) CPU threads.
@article{arxiv.2210.17093,
title = {GPU acceleration of many-body perturbation theory methods in MOLGW with OpenACC},
author = {Young-Moo Byun and Jejoong Yoo},
journal= {arXiv preprint arXiv:2210.17093},
year = {2023}
}