Charles S. Callahan, Sean M. Bresler, Sean C. Coburn, David A. Long, Gregory B. Rieker
{"title":"GAAS: GPU accelerated absorption simulator","authors":"Charles S. Callahan, Sean M. Bresler, Sean C. Coburn, David A. Long, Gregory B. Rieker","doi":"10.1016/j.jqsrt.2024.109307","DOIUrl":null,"url":null,"abstract":"Interpreting measured absorption spectroscopy data can require repeated simulations of the expected absorption spectrum to fit the data. In cases of high temperature or broadband spectra, the computational load of the spectral analysis can be expensive due to the large number of individual absorption transitions that contribute to each simulation. We present a Graphics Processing Unit (GPU) Accelerated Absorption Simulator (GAAS) – a fast, hardware-accelerated, line-by-line absorption simulation software for generating absorption spectra based on Voigt and Hartmann-Tran lineshape profiles. We show that GAAS produces the same output spectra as the <ce:italic>hi</ce:italic>gh-resolution <ce:italic>trans</ce:italic>mission molecular absorption database (HITRAN) Application Programming Interface (HAPI) to within 32-bits of numerical precision for spectra based on both Voigt and Hartmann-Tran profiles. We also measure the performance increase compared to HAPI and demonstrate that GAAS can reduce simulation time by up to 115x for spectra containing many (several thousand or more) absorption transitions. The software is provided as an open-source python library which is built around an OpenCL implementation of the Voigt and Hartmann-Tran lineshape functions. GAAS can be run on a variety of GPU hardware including integrated GPUs on most computers and high-performance external GPUs. It is installed as a standalone Python library, making it accessible and easy to use for many applications. GAAS will enable researchers to more efficiently analyze complex spectra, especially using advanced lineshapes, to ultimately increase the accuracy of complex spectroscopic measurements.","PeriodicalId":16935,"journal":{"name":"Journal of Quantitative Spectroscopy & Radiative Transfer","volume":"134 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Spectroscopy & Radiative Transfer","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1016/j.jqsrt.2024.109307","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Interpreting measured absorption spectroscopy data can require repeated simulations of the expected absorption spectrum to fit the data. In cases of high temperature or broadband spectra, the computational load of the spectral analysis can be expensive due to the large number of individual absorption transitions that contribute to each simulation. We present a Graphics Processing Unit (GPU) Accelerated Absorption Simulator (GAAS) – a fast, hardware-accelerated, line-by-line absorption simulation software for generating absorption spectra based on Voigt and Hartmann-Tran lineshape profiles. We show that GAAS produces the same output spectra as the high-resolution transmission molecular absorption database (HITRAN) Application Programming Interface (HAPI) to within 32-bits of numerical precision for spectra based on both Voigt and Hartmann-Tran profiles. We also measure the performance increase compared to HAPI and demonstrate that GAAS can reduce simulation time by up to 115x for spectra containing many (several thousand or more) absorption transitions. The software is provided as an open-source python library which is built around an OpenCL implementation of the Voigt and Hartmann-Tran lineshape functions. GAAS can be run on a variety of GPU hardware including integrated GPUs on most computers and high-performance external GPUs. It is installed as a standalone Python library, making it accessible and easy to use for many applications. GAAS will enable researchers to more efficiently analyze complex spectra, especially using advanced lineshapes, to ultimately increase the accuracy of complex spectroscopic measurements.
期刊介绍:
Papers with the following subject areas are suitable for publication in the Journal of Quantitative Spectroscopy and Radiative Transfer:
- Theoretical and experimental aspects of the spectra of atoms, molecules, ions, and plasmas.
- Spectral lineshape studies including models and computational algorithms.
- Atmospheric spectroscopy.
- Theoretical and experimental aspects of light scattering.
- Application of light scattering in particle characterization and remote sensing.
- Application of light scattering in biological sciences and medicine.
- Radiative transfer in absorbing, emitting, and scattering media.
- Radiative transfer in stochastic media.