Pulsar acceleration searches on the GPU for the Square Kilometre Array

Pulsar acceleration searches are methods for recovering signals from radio telescopes, that may otherwise be lost due to the effect of orbital acceleration in binary systems. The vast amount of data that will be produced by next generation instruments such as the Square Kilometre Array (SKA) necessitates real-time acceleration searches, which in turn requires the use of HPC platforms. We present our implementation of the Fourier Domain Acceleration Search (FDAS) algorithm on Graphics Processor Units (GPUs) in the context of the SKA, as part of the Astro-Accelerate real-time data processing library, currently under development at the Oxford e-Research Centre (OeRC), University of Oxford

Searching for pulsars in extreme orbits — GPU acceleration of the Fourier domain 'jerk' search

Binary pulsars are an important target for radio surveys because they present a natural laboratory for a wide range of astrophysics for example testing general relativity, including detection of gravitational waves. The orbital motion of a pulsar which is locked in a binary system causes a frequency shift (a Doppler shift) in their normally very periodic pulse emissions. These shifts cause a reduction in the sensitivity of traditional periodicity searches. To correct this smearing Ransom [2001], Ransom et al. [2002] developed the Fourier domain acceleration search (FDAS) which uses a matched filtering technique. This method is however limited to a constant pulsar acceleration. Therefore, Andersen and Ransom [2018] broadened the Fourier domain acceleration search to account also for a linear change in the acceleration by implementing the Fourier domain "jerk" search into the PRESTO software package. This extension increases the number of matched filters used significantly. We have implemented the Fourier domain "jerk" search (JERK) on GPUs using CUDA. We have achieved 90x performance increase when compared to the parallel implementation of JERK in PRESTO. This work is part of the AstroAccelerate project Armour et al. [2019], a many-core accelerated time-domain signal processing library for radio astronomy

Multi-year application of the three-dimensional numerical generation of response factors (NGRF) method in the prediction of conductive temperatures in soil and passive cooling earth-contact components

A recently developed method named the three-dimensional numerical generation of response factors NGRF (Zoras and Kosmopoulos, 2009) was claimed to be fast, accurate and flexible as a result of incorporating elements of the response factor method into a finite volume technique based numerical model. The presented paper reports on the application of the NGRF method for the numerical prediction of temperatures within and around structural passive cooling components over multi-year temperature profiles. Once the numerical temperature response factors time series of an earth-contact component's grid node had been generated then its future thermal performance due to any surrounding temperature variation can be predicted fast and accurately. The NGRF method was, successfully, applied through an intermodel testing procedure to simulate soil and structural earth-contact passive cooling component temperatures for multiple years. © 2011 Elsevier Ltd

A GPU implementation of the correlation technique for real-time Fourier domain pulsar acceleration searches

The study of binary pulsars enables tests of general relativity. Orbital motion in binary systems causes the apparent pulsar spin frequency to drift, reducing the sensitivity of periodicity searches. Acceleration searches are methods that account for the effect of orbital acceleration. Existing methods are currently computationally expensive, and the vast amount of data that will be produced by next-generation instruments such as the Square Kilometre Array necessitates real-time acceleration searches, which in turn requires the use of high-performance computing (HPC) platforms. We present our implementation of the correlation technique for the Fourier Domain Acceleration Search (FDAS) algorithm on Graphics Processor Units (GPUs). The correlation technique is applied as a convolution with multiple finite impulse response (FIR) filters in the Fourier domain. Two approaches are compared: the first uses the NVIDIA cuFFT library for applying Fast Fourier transforms (FFTs) on the GPU, and the second contains a custom FFT implementation in GPU shared memory. We find that the FFT shared-memory implementation performs between 1.5 and 3.2 times faster than our cuFFT-based application for smaller but sufficient filter sizes. It is also 4–6 times faster than the existing GPU and OpenMP implementations of FDAS. This work is part of the AstroAccelerate project, a many-core accelerated time-domain signal-processing library for radio astronomy