PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars

Abstract The Fourier domain jerk search algorithm, an integral component of the PRESTO software suite, has emerged as a key tool for detecting binary pulsars. However, it is a CPU-based jerk search and is a very computationally expensive process, particularly when exploring a broad range of search parameters. In order to address this challenge, we have developed PrestoZL, a GPU-accelerated, high-throughput jerk search toolkit. PrestoZL introduces an innovative GPU parallel design for the jerk search algorithm to mitigate performance degradation caused by memory-intensive operations. We have also developed a pipelined version of PrestoZL, which adds fine-grained orchestration to the CPU–GPU execution pipeline to alleviate the GPU stall problem during the search. The experiment conducted on a 30 minute observation using a machine equipped with an A100-40G GPU and 20 i7-12700K CPUs, shows that PrestoZL achieves an end-to-end speedup of 56.38× over a CPU-based jerk search in PRESTO with OpenMP. PrestoZL achieves search results that are fully identical to the CPU-based jerk search in PRESTO, including the number of detected pulsars, as well as the output search parameters and signal-to-noise ratio values.

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Publication Details

Journal
The Astrophysical Journal Supplement Series
Published
2025-09-01
DOI
https://doi.org/10.3847/1538-4365/adf4e5
Citations
1
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
1.15
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article

PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars

S. M. Ransom, Yi Feng, X Tang, Donghui Quan et al.
1 citations
The Astrophysical Journal Supplement Series
Pulsars and Gravitational Waves Research
1.15
article

PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars

S. M. Ransom, Yi Feng, X Tang, Donghui Quan, Qi Wang, Huaxi Chen, Katherine Mao, Qiuhong Pan, Lei Chen, Di Li, Pei Wang, Zujie Ren, Zhaorong Tang
article en
1 citations

Abstract

Abstract The Fourier domain jerk search algorithm, an integral component of the PRESTO software suite, has emerged as a key tool for detecting binary pulsars. However, it is a CPU-based jerk search and is a very computationally expensive process, particularly when exploring a broad range of search parameters. In order to address this challenge, we have developed PrestoZL, a GPU-accelerated, high-throughput jerk search toolkit. PrestoZL introduces an innovative GPU parallel design for the jerk search algorithm to mitigate performance degradation caused by memory-intensive operations. We have also developed a pipelined version of PrestoZL, which adds fine-grained orchestration to the CPU–GPU execution pipeline to alleviate the GPU stall problem during the search. The experiment conducted on a 30 minute observation using a machine equipped with an A100-40G GPU and 20 i7-12700K CPUs, shows that PrestoZL achieves an end-to-end speedup of 56.38× over a CPU-based jerk search in PRESTO with OpenMP. PrestoZL achieves search results that are fully identical to the CPU-based jerk search in PRESTO, including the number of detected pulsars, as well as the output search parameters and signal-to-noise ratio values.

The Astrophysical Journal Supplement SeriesVol. 280(1)
Openalex Percentile: Top 17%
Pulsars and Gravitational Waves Research
1.15
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PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars — S. M. Ransom, Yi Feng, et al. · The Astrophysical Journal Supplement Series (2025) | TGRS Research Map | TGRS