Galmoss: A package for GPU-accelerated galaxy profile fitting

IF 1.9 4区物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS

Astronomy and Computing Pub Date : 2024-04-01 DOI:10.1016/j.ascom.2024.100825

Mi Chen , Rafael S. de Souza , Quanfeng Xu , Shiyin Shen , Ana L. Chies-Santos , Renhao Ye , Marco A. Canossa-Gosteinski , Yanping Cong

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引用次数: 0

Abstract

We introduce galmoss, a python-based, torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, galmoss meets the high computational demands of large-scale galaxy surveys, placing galaxy profile fitting in the CSST/LSST-era. It incorporates widely used profiles such as the Sérsic, Exponential disk, Ferrer, King, Gaussian, and Moffat profiles, and allows for the easy integration of more complex models. Tested on 8289 galaxies from the Sloan Digital Sky Survey (SDSS) g-band with a single NVIDIA A100 GPU, galmoss completed classical Sérsic profile fitting in about 10 min. Benchmark tests show that galmoss achieves computational speeds that are 6 $\times$ faster than those of default implementations.

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Galmoss：用于 GPU 加速星系剖面拟合的软件包

我们介绍了galmoss，一个基于python、由火炬驱动的二维星系剖面拟合工具。通过无缝启用 GPU 并行化，galmoss 可以满足大规模星系调查的高计算要求，将星系剖面拟合置于 CSST/LSST 时代。它整合了广泛使用的剖面图，如塞西克剖面图、指数盘剖面图、费雷尔剖面图、金剖面图、高斯剖面图和莫法特剖面图，并允许轻松整合更复杂的模型。通过对斯隆数字巡天（SDSS）g波段的8289个星系进行测试，使用单个NVIDIA A100 GPU，galmoss在大约10分钟内就完成了经典的Sérsic剖面拟合。基准测试表明，galmoss的计算速度比默认实现快6倍。

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来源期刊

Astronomy and Computing ASTRONOMY & ASTROPHYSICSCOMPUTER SCIENCE,-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

CiteScore

4.10

自引率

8.00%

发文量

期刊介绍： Astronomy and Computing is a peer-reviewed journal that focuses on the broad area between astronomy, computer science and information technology. The journal aims to publish the work of scientists and (software) engineers in all aspects of astronomical computing, including the collection, analysis, reduction, visualisation, preservation and dissemination of data, and the development of astronomical software and simulations. The journal covers applications for academic computer science techniques to astronomy, as well as novel applications of information technologies within astronomy.