Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method

With the rapidly increasing rate of microlensing planet detections, microlensing modeling software faces significant challenges in computation efficiency. Here, we develop the Twinkle code, an efficient and robust binary-lens modeling software suite optimized for heterogeneous computing devices, esp...

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Main Authors: Suwei Wang, Lile Wang, Subo Dong
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Online Access:https://doi.org/10.3847/1538-4365/ad9b8d
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author Suwei Wang
Lile Wang
Subo Dong
author_facet Suwei Wang
Lile Wang
Subo Dong
author_sort Suwei Wang
collection DOAJ
description With the rapidly increasing rate of microlensing planet detections, microlensing modeling software faces significant challenges in computation efficiency. Here, we develop the Twinkle code, an efficient and robust binary-lens modeling software suite optimized for heterogeneous computing devices, especially GPUs. Existing microlensing codes have the issue of catastrophic cancellation that undermines the numerical stability and precision, and Twinkle resolves them by refining the coefficients of the binary-lens equation. We also devise an improved method for robustly identifying ghost images, thereby enhancing computational reliability. We have advanced the state of the art by optimizing Twinkle specifically for heterogeneous computing devices by taking into account the unique task and cache memory dispatching patterns of GPUs, while the compatibility with the traditional computing architectures of CPUs is still maintained. Twinkle has demonstrated an acceleration of approximately 2 orders of magnitude (≳10 ^2 ×) on contemporary GPUs. The enhancement in computational speed of Twinkle will translate to the delivery of accurate and highly efficient data analysis for ongoing and upcoming microlensing projects. Both GPU and CPU versions of Twinkle are open-source and publicly available.
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institution Kabale University
issn 0067-0049
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spelling doaj-art-3589cdf5bbfa426281344948f062a67d2025-01-15T08:43:34ZengIOP PublishingThe Astrophysical Journal Supplement Series0067-00492025-01-0127624010.3847/1538-4365/ad9b8dTwinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration MethodSuwei Wang0https://orcid.org/0009-0008-3668-9045Lile Wang1https://orcid.org/0000-0002-6540-7042Subo Dong2https://orcid.org/0000-0002-1027-0990The Kavli Institute for Astronomy and Astrophysics, Peking University , Beijing 100871, People’s Republic of China ; suwei_wang@stu.pku.edu.cn, lilew@pku.edu.cn; Department of Astronomy, School of Physics, Peking University , Beijing 100871, People’s Republic of China ; dongsubo@pku.edu.cnThe Kavli Institute for Astronomy and Astrophysics, Peking University , Beijing 100871, People’s Republic of China ; suwei_wang@stu.pku.edu.cn, lilew@pku.edu.cn; Department of Astronomy, School of Physics, Peking University , Beijing 100871, People’s Republic of China ; dongsubo@pku.edu.cnThe Kavli Institute for Astronomy and Astrophysics, Peking University , Beijing 100871, People’s Republic of China ; suwei_wang@stu.pku.edu.cn, lilew@pku.edu.cn; Department of Astronomy, School of Physics, Peking University , Beijing 100871, People’s Republic of China ; dongsubo@pku.edu.cn; National Astronomical Observatories, Chinese Academy of Science , Beijing 100101, People’s Republic of ChinaWith the rapidly increasing rate of microlensing planet detections, microlensing modeling software faces significant challenges in computation efficiency. Here, we develop the Twinkle code, an efficient and robust binary-lens modeling software suite optimized for heterogeneous computing devices, especially GPUs. Existing microlensing codes have the issue of catastrophic cancellation that undermines the numerical stability and precision, and Twinkle resolves them by refining the coefficients of the binary-lens equation. We also devise an improved method for robustly identifying ghost images, thereby enhancing computational reliability. We have advanced the state of the art by optimizing Twinkle specifically for heterogeneous computing devices by taking into account the unique task and cache memory dispatching patterns of GPUs, while the compatibility with the traditional computing architectures of CPUs is still maintained. Twinkle has demonstrated an acceleration of approximately 2 orders of magnitude (≳10 ^2 ×) on contemporary GPUs. The enhancement in computational speed of Twinkle will translate to the delivery of accurate and highly efficient data analysis for ongoing and upcoming microlensing projects. Both GPU and CPU versions of Twinkle are open-source and publicly available.https://doi.org/10.3847/1538-4365/ad9b8dGravitational microlensing exoplanet detectionBinary lens microlensingFinite-source photometric effectGPU computingOpen source software
spellingShingle Suwei Wang
Lile Wang
Subo Dong
Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
The Astrophysical Journal Supplement Series
Gravitational microlensing exoplanet detection
Binary lens microlensing
Finite-source photometric effect
GPU computing
Open source software
title Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
title_full Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
title_fullStr Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
title_full_unstemmed Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
title_short Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method
title_sort twinkle a gpu based binary lens microlensing code with the contour integration method
topic Gravitational microlensing exoplanet detection
Binary lens microlensing
Finite-source photometric effect
GPU computing
Open source software
url https://doi.org/10.3847/1538-4365/ad9b8d
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