GPU acceleration of many‐body perturbation theory methods in MOLGW with OpenACC

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 9.7×$$ 9.7\times $$ over 32 open multi‐processing (OpenMP) CPU threads. Quasiparticle self‐consistent many‐body perturbation theory (MBPT) methods implemented in MOLGW, a central processing unit (CPU) code for MBPT calculations of electronic excitations in molecules, are accelerated on graphics processing units (GPUs), which enables the application of predictive MBPT methods without depending on the choice of starting points to large systems.