Real-time, fast radio transient searches with GPU de-dispersion

TL;DR

This paper demonstrates how GPUs can be used for real-time detection of fast radio transients, significantly speeding up the de-dispersion process compared to traditional methods.

Contribution

The authors present a GPU-based solution for real-time de-dispersion in radio transient searches, achieving a 50 to 200 times speed-up over conventional software.

Findings

GPU solution offers 50-200x speed-up

Real-time transient detection is feasible with GPU hardware

Performance comparisons show significant improvements over traditional methods

Abstract

The identification, and subsequent discovery, of fast radio transients through blind-search surveys requires a large amount of processing power, in worst cases scaling as $\mathcal{O}(N^3)$. For this reason, survey data are generally processed offline, using high-performance computing architectures or hardware-based designs. In recent years, graphics processing units have been extensively used for numerical analysis and scientific simulations, especially after the introduction of new high-level application programming interfaces. Here we show how GPUs can be used for fast transient discovery in real-time. We present a solution to the problem of de-dispersion, providing performance comparisons with a typical computing machine and traditional pulsar processing software. We describe the architecture of a real-time, GPU-based transient search machine. In terms of performance, our GPU solution provides a speed-up factor of between 50 and 200, depending on the parameters of the search.