Bits missing: Finding exotic pulsars using bfloat16 on NVIDIA GPUs
Jack White, Karel Adamek, Jayanta Roy, Sofia Dimoudi, Scott M. Ransom,, Wesley Armour

TL;DR
This paper evaluates the impact of using bfloat16 precision in GPU-accelerated pulsar detection, showing minimal sensitivity loss and a 1.6x speedup over single-precision methods.
Contribution
It introduces a modified FDAS pipeline using bfloat16 precision on GPUs, demonstrating comparable detection accuracy with significant performance gains.
Findings
bfloat16 peaks within 3% of single-precision SNR
97.53% of bright peaks match in bfloat16 and single-precision
bfloat16 achieves 1.6x speedup over single-precision
Abstract
The Fourier Domain Acceleration Search (FDAS) is an effective technique for detecting faint binary pulsars in large radio astronomy datasets. This paper quantifies the sensitivity impact of reducing numerical precision in the GPU accelerated FDAS pipeline of the AstroAccelerate 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 FFTs. AstroAccelerate has been modified to use bfloat16 (and IEEE754 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 and double-precision convolutions. All…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRadio Astronomy Observations and Technology · Pulsars and Gravitational Waves Research · Superconducting and THz Device Technology
