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

  • Kuang Mao
  • , Zhaorong Tang
  • , Qiuhong Pan*
  • , Pei Wang
  • , Huaxi Chen
  • , Scott M. Ransom
  • , Di Li
  • , Xuefei Tang
  • , Qi Wang
  • , Yi Feng
  • , Lei Chen
  • , Donghui Quan
  • , Zujie Ren
  • *Corresponding author for this work
  • Zhejiang Lab
  • CAS - National Astronomical Observatories
  • Beijing Normal University
  • National Science Foundation
  • Tsinghua University
  • Research Center for Astronomical Computing

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Article number36
JournalAstrophysical Journal, Supplement Series
Volume280
Issue number1
DOIs
Publication statusPublished - 1 Sept 2025
Externally publishedYes

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