  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
(SKA) 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
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 to 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.
