CUDA implementation of an optimal online Gaussian-Signal-in-Gaussian-Noise detector

Nir Nossenson*, Ariel J. Jaffe

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageAmerican English
Title of host publication2016 IEEE High Performance Extreme Computing Conference, HPEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035250
DOIs
StatePublished - 28 Nov 2016
Externally publishedYes
Event2016 IEEE High Performance Extreme Computing Conference, HPEC 2016 - Waltham, United States
Duration: 13 Sep 201615 Sep 2016

Publication series

Name2016 IEEE High Performance Extreme Computing Conference, HPEC 2016

Conference

Conference2016 IEEE High Performance Extreme Computing Conference, HPEC 2016
Country/TerritoryUnited States
CityWaltham
Period13/09/1615/09/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • CUDA
  • Detection
  • Electrophysiological Signals
  • Gaussian Signal in Gaussian Noise
  • Radar
  • Sonar
  • parallel computing

Fingerprint

Dive into the research topics of 'CUDA implementation of an optimal online Gaussian-Signal-in-Gaussian-Noise detector'. Together they form a unique fingerprint.

Cite this