A Real-time Single Pulse Detection Algorithm for GPUs

TL;DR

This paper presents a GPU-based single pulse detection algorithm for radio astronomy that significantly accelerates the processing of fast radio burst data, enabling real-time analysis on large datasets.

Contribution

The authors developed a GPU implementation of a single pulse detection algorithm that is 17 times faster than CPU code, enabling real-time processing of SKA-like data.

Findings

GPU algorithm is 17x faster than CPU implementation.

The code enables real-time single pulse searches on large datasets.

The implementation is part of the AstroAccelerate project for radio astronomy.

Abstract

The detection of non-repeating events in the radio spectrum has become an important area of study in radio astronomy over the last decade due to the discovery of fast radio bursts (FRBs). We have implemented a single pulse detection algorithm, for NVIDIA GPUs, which use boxcar filters of varying widths. Our code performs the calculation of standard deviation, matched filtering by using boxcar filters and thresholding based on the signal-to-noise ratio. We present our parallel implementation of our single pulse detection algorithm. Our GPU algorithm is approximately 17x faster than our current CPU OpenMP code (NVIDIA Titan XP vs Intel E5-2650v3). This code is part of the AstroAccelerate project which is a many-core accelerated time-domain signal processing code for radio astronomy. This work allows our AstroAccelerate code to perform a single pulse search on SKA-like data 4.3x faster than real-time.