A Comparison of Accelerator Architectures for Radio-Astronomical Signal-Processing Algorithms

In this paper, we compare a wide range of accelerator architectures (GPUs from AMD and NVIDIA, the Xeon Phi, and a DSP), by means of a signal-processing pipeline that processes radio-telescope data. We discuss the mapping of the algorithms from this pipeline to the accelerators, and analyze performance. We also analyze energy efficiency, using custom-built, microcontroller-based power sensors that measure the instantaneous power consumption of the accelerators, at millisecond time scale. We show that the GPUs are the fastest and most energy efficient accelerators, and that the differences in performance and energy efficiency are large.