A Novel Greedy Approach To Harmonic Summing Using GPUs

TL;DR

This paper introduces GPU-optimized algorithms for incoherent harmonic summing in radio astronomy, improving sensitivity and performance in Fourier domain periodicity searches for pulsar detection.

Contribution

It presents novel GPU-compatible algorithms for harmonic summing, addressing memory access challenges and enhancing processing efficiency in radio astronomy data analysis.

Findings

Improved sensitivity in pulsar detection

Enhanced GPU performance for harmonic summing

Algorithms suited for many-core architectures

Abstract

Incoherent harmonic summing is a technique which is used to improve the sensitivity of Fourier domain search methods. A one dimensional harmonic sum is used in time-domain radio astronomy as part of the Fourier domain periodicity search, a type of search used to detect isolated single pulsars. The main problem faced when implementing the harmonic sum on many-core architectures, like GPUs, is the very unfavourable memory access pattern of the harmonic sum algorithm. The memory access pattern gets worse as the dimensionality of the harmonic sum increases. Here we present a set of algorithms for calculating the harmonic sum that are suited to many-core architectures such as GPUs. We present an evaluation of the sensitivity of these different approaches, and their performance. This work forms part of the AstroAccelerate project which is a GPU accelerated software package for processing time-domain radio astronomy data.