@inproceedings{203500e891224b2f8125fc92c9155813,
title = "CUDA implementation of an optimal online Gaussian-Signal-in-Gaussian-Noise detector",
abstract = "We address the computationally demanding task of real time optimal detection of a Gaussian Signal in Gaussian Noise. The mathematical principles of such a detector were formulated in 1965, but a full real-time implementation of these principles was not possible for decades mainly due to technological barriers. We present a CUDA based implementation of such an optimal detector and study its decision making speed (or throughput) as function of target signal duration and signal filter length. We also compare the throughput results to those of a CPU based design. We report on detection rates ranging from 3.5 KHz for a target duration of 10756 samples up to 15.6 KHz for target duration of 92 samples. The CUDA based detector running on 384 parallel cores had a superior throughput comparing to a pure CPU implementation when target duration was longer than 600 samples.",
keywords = "CUDA, Detection, Electrophysiological Signals, Gaussian Signal in Gaussian Noise, Radar, Sonar, parallel computing",
author = "Nir Nossenson and Jaffe, \{Ariel J.\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE High Performance Extreme Computing Conference, HPEC 2016 ; Conference date: 13-09-2016 Through 15-09-2016",
year = "2016",
month = nov,
day = "28",
doi = "10.1109/HPEC.2016.7761613",
language = "الإنجليزيّة",
series = "2016 IEEE High Performance Extreme Computing Conference, HPEC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE High Performance Extreme Computing Conference, HPEC 2016",
address = "الولايات المتّحدة",
}