Single Pulse Detection Algorithms for Real-time Fast Radio Burst Searches using GPUs
Karel Adamek, Wesley Armour

TL;DR
This paper introduces new GPU-based algorithms for real-time single pulse detection in radio astronomy, optimizing speed with minimal signal loss, suitable for large data volumes from modern telescopes.
Contribution
The authors develop and implement two novel lossy algorithms for single pulse detection using boxcar filters on GPUs, achieving significant speedups with controlled signal loss.
Findings
Processing speed 266x faster than real-time on P100 GPU
Achieved 500x real-time processing on Titan V GPU
Mean signal power loss of 7% with the new algorithms
Abstract
The detection of non-repeating or irregular events in time-domain radio astronomy has gained importance over the last decade due to the discovery of fast radio bursts. Existing or upcoming radio telescopes are gathering more and more data and consequently the software, which is an important part of these telescopes, must process large data volumes at high data rates. Data has to be searched through to detect new and interesting events, often in real-time. These requirements necessitate new and fast algorithms which must process data quickly and accurately. In this work we present new algorithms for single pulse detection using boxcar filters. We have quantified the signal loss introduced by single pulse detection algorithms which use boxcar filters and based on these results, we have designed two distinct "lossy" algorithms. Our lossy algorithms use an incomplete set of boxcar filters…
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