Abstract
We developed a GPU based single-pulse search pipeline (GSP) with a candidate-archiving database. Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit (PRESTO), GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database. We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey (CRAFTS), which resulted in quasi-real-time processing. The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients (RRATs) and fast radio bursts (FRBs). We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band (UWB) receiver. GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB. GSP also discovered 13 new pulsars. We measured the computational efficiency of GSP to be ∼120 times faster than the original PRESTO and ∼60 times faster than an MPI-parallelized version of PRESTO.
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