Performance Analysis of Noise Subspace-based Narrowband Direction-of-Arrival (DOA) Estimation Algorithms on CPU and GPU

July 28, 2020 · Entered Twilight · 🏛 arXiv.org

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Repo contents: Eigen.rar, MUSIC_cuda.cu, README.md, TestData, helper_cuda.h, helper_cusolver.h, helper_string.h, images

Authors Hamza Eray, Alptekin Temizel arXiv ID 2007.14135 Category cs.DC: Distributed Computing Cross-listed eess.SP Citations 2 Venue arXiv.org Repository https://github.com/erayhamza/NssDOACuda ⭐ 15 Last Checked 2 months ago

Abstract

High-performance computing of array signal processing problems is a critical task as real-time system performance is required for many applications. Noise subspace-based Direction-of-Arrival (DOA) estimation algorithms are popular in the literature since they provide higher angular resolution and higher robustness. In this study, we investigate various optimization strategies for high-performance DOA estimation on GPU and comparatively analyze alternative implementations (MATLAB, C/C++ and CUDA). Experiments show that up to 3.1x speedup can be achieved on GPU compared to the baseline multi-threaded CPU implementation. The source code is publicly available at the following link: https://github.com/erayhamza/NssDOACuda