{"title":"GPU acceleration of many-body perturbation theory methods in MOLGW with OpenACC","authors":"Young-Moo Byun, Jejoong Yoo","doi":"10.1002/qua.27345","DOIUrl":null,"url":null,"abstract":"<p>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 <math>\n <semantics>\n <mrow>\n <mn>9</mn>\n <mo>.</mo>\n <mn>7</mn>\n <mo>×</mo>\n </mrow>\n <annotation>$$ 9.7\\times $$</annotation>\n </semantics></math> over 32 open multi-processing (OpenMP) CPU threads.</p>","PeriodicalId":182,"journal":{"name":"International Journal of Quantum Chemistry","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Quantum Chemistry","FirstCategoryId":"92","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/qua.27345","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
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 over 32 open multi-processing (OpenMP) CPU threads.
期刊介绍:
Since its first formulation quantum chemistry has provided the conceptual and terminological framework necessary to understand atoms, molecules and the condensed matter. Over the past decades synergistic advances in the methodological developments, software and hardware have transformed quantum chemistry in a truly interdisciplinary science that has expanded beyond its traditional core of molecular sciences to fields as diverse as chemistry and catalysis, biophysics, nanotechnology and material science.