Weather radar data processing on graphic cards

Weather radar operation generates data at a high rate that requires prompt processing. The operations performed on data for weather product generation are repeated in each resolution cell and thus are naturally prone to parallelization. Parallel processing using graphic cards is an emerging technology that allows for implementation of high-throughput algorithms at a low cost. In this paper, the parallel implementation of the main product of a polarimetric weather radar using GPU is presented, focusing on its optimization. A speedup exceeding 20×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document} is obtained when compared to the serial implementation. Also processing is found to be memory bound, which results in a counter-intuitive performance improvement when the number of threads per job is reduced.