论文标题
openACC molgw中多体扰动理论方法的GPU加速度
GPU acceleration of many-body perturbation theory methods in MOLGW with OpenACC
论文作者
论文摘要
Quasiparticle自洽多体扰动理论（MBPT）方法更新特征值和特征向量可以计算分子系统的激发态性能，而不取决于起点的选择。但是，这些方法即使在现代的多核中央处理单元（CPU）上也是计算密集的，因此通常仅限于小型系统。多核加速器（例如图形处理单元（GPU））可能能够提高这些方法的性能而不会失去准确性，从而使独立于起点的MBPT方法适用于大型系统。在这里，我们GPU加速了Molgw，这是一种基于高斯的MBPT分子代码，带有开放式加速器（OpenACC），并在32个开放的多处理（OpenMP）CPU线程上实现高达9.7倍的加速度。
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.
