Bits missing: finding exotic pulsars using bfloat16 on NVIDIA GPUs

The Fourier domain acceleration search (FDAS) is an effective technique for detecting faint binary pulsars in large radio astronomy data sets. This paper quantifies the sensitivity impact of reducing numerical precision in the graphics processing unit (GPU)-accelerated FDAS pipeline of the AstroAccelerate (AA) software package. The prior implementation used IEEE-754 single-precision in the entire binary pulsar detection pipeline, spending a large fraction of the runtime computing GPU-accelerated fast Fourier transforms. AA has been modified to use bfloat16 (and IEEE-754 double-precision to provide a “gold standard” comparison) within the Fourier domain convolution section of the FDAS routine. Approximately 20,000 synthetic pulsar filterbank files representing binary pulsars were generated using SIGPROC with a range of physical parameters. They have been processed using bfloat16, single-precision, and double-precision convolutions. All bfloat16 peaks are within 3% of the predicted signal-to-noise ratio of their corresponding single-precision peaks. Of 14,971 “bright” single-precision fundamental peaks above a power of 44.982 (our experimentally measured highest noise value), 14,602 (97.53%) have a peak in the same acceleration and frequency bin in the bfloat16 output plane, while in the remaining 369 the nearest peak is located in the adjacent acceleration bin. There is no bin drift measured between the single- and double-precision results. The bfloat16 version of FDAS achieves a speedup of approximately 1.6× compared to single-precision. A comparison between AA and the PRESTO software package is presented using observations collected with the GMRT of PSR J1544+4937, a 2.16 ms black widow pulsar in a 2.8 hr compact orbit

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