This talk will present research on accelerator-based computing for radio telescopes. Showing GPU implementations of a dozen of (signal-processing) algorithms used by radio telescopes, e.g., filtering, correlating, beam forming, dedispersion, and peak detection. Glued together, these computational kernels form several processing pipelines. Each pipeline implements an observation mode, as used by the LOFAR radio telescope. Implemented pipelines create sky images, to search for pulsars, to observe known pulsars, and to detect ultra-high-energy particles - first on a Blue Gene/P, and ported these to GPUs. This talk will briefly explain these algorithms and processing pipelines, show performance results, multi-GPU scaling results, and impact on energy efficiency. The research is relevant to current radio telescopes like LOFAR, and the future SKA telescope, that needs exascale computing power.
In this talk, we will present GPU implementations of four highly compute-intensive algorithms used by radio telescopes.