Modern radio telescopes like the Square Kilometer Array (SKA) will need to process in real-time exabytes of radio-astronomical signals to construct a high-resolution map of the sky. Near-Memory Computing (NMC) could alleviate the performance bottlenecks due to frequent memory accesses in a state-of-the-art radio-astronomy imaging algorithm. In this paper, we show that a sub-module performing a two-dimensional fast Fourier transform (2D FFT) is memory bound using CPI breakdown analysis on IBM Power9. Then, we present an NMC approach on FPGA for 2D FFT that outperforms a CPU by up to a factor of 120x and performs comparably to a high-end GPU, while using less bandwidth and memory.
@article{arxiv.2005.04098,
title = {Near Memory Acceleration on High Resolution Radio Astronomy Imaging},
author = {Stefano Corda and Bram Veenboer and Ahsan Javed Awan and Akash Kumar and Roel Jordans and Henk Corporaal},
journal= {arXiv preprint arXiv:2005.04098},
year = {2020}
}