Efficient heterogeneous parallel programming for compressed sensing based direction of arrival estimation

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buir.contributor.authorGüngör, Alper
buir.contributor.orcidGüngör, Alper|0000-0002-3043-9124
buir.contributor.orcidKılıç, Berkan|0000-0003-0367-4329
dc.citation.epage14en_US
dc.citation.issueNumbere6490en_US
dc.citation.spage1en_US
dc.citation.volumeNumberEarly Viewen_US
dc.contributor.authorFişne, A.
dc.contributor.authorKılıç, Berkan
dc.contributor.authorGüngör, Alper
dc.contributor.authorÖzsoy, A.
dc.date.accessioned2022-02-02T11:24:34Z
dc.date.available2022-02-02T11:24:34Z
dc.date.issued2021-07
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractIn the direction of arrival (DoA) estimation, typically sensor arrays are used where the number of required sensors can be large depending on the application. With the help of compressed sensing (CS), hardware complexity of the sensor array system can be reduced since reliable estimations are possible by using the compressed measurements where the compression is done by measurement matrices. After the compression, DoAs are reconstructed by using sparsity promoting algorithms such as alternating direction method of multipliers (ADMM). For the given procedure, both the measurement matrix design and the reconstruction algorithm may include computationally intensive operations, which are addressed in this study. The presented simulation results imply the feasibility of the system in real-time processing with energy efficient implementations. We propose employing parallel programming to satisfy the real-time processing requirements. While the measurement matrix design has been accelerated 16urn:x-wiley:cpe:media:cpe6490:cpe6490-math-0001 with CPU based parallel version with respect to the fastest serial implementation, ADMM based DoA estimation has been improved 1.1urn:x-wiley:cpe:media:cpe6490:cpe6490-math-0002 with GPU based parallel version compared to the fastest CPU parallel implementation. In addition, we achieved, to the best of our knowledge, the first energy-efficient real-time DoA estimation on embedded Jetson GPGPUs in 15 W power consumption without affecting the DoA accuracy performance.en_US
dc.description.provenanceSubmitted by Samet Emre (samet.emre@bilkent.edu.tr) on 2022-02-02T11:24:34Z No. of bitstreams: 1 Efficient_heterogeneous_parallel_programming_for_compressed_sensing_based_direction_of_arrival_estimation.pdf: 828197 bytes, checksum: 22cefb9d961b33145920c7500010c03f (MD5)en
dc.description.provenanceMade available in DSpace on 2022-02-02T11:24:34Z (GMT). No. of bitstreams: 1 Efficient_heterogeneous_parallel_programming_for_compressed_sensing_based_direction_of_arrival_estimation.pdf: 828197 bytes, checksum: 22cefb9d961b33145920c7500010c03f (MD5) Previous issue date: 2021-07en
dc.identifier.doi10.1002/cpe.6490en_US
dc.identifier.issn1532-0626
dc.identifier.urihttp://hdl.handle.net/11693/76967
dc.language.isoEnglishen_US
dc.publisherJohn Wiley & Sons Ltd.en_US
dc.relation.isversionofhttps://doi.org/10.1002/cpe.6490en_US
dc.source.titleConcurrency and Computation: Practice and Experienceen_US
dc.subjectCompressed sensingen_US
dc.subjectDirection of arrival estimationen_US
dc.subjectEmbedded GPGPUen_US
dc.subjectParallel programmingen_US
dc.subjectReal time computingen_US
dc.titleEfficient heterogeneous parallel programming for compressed sensing based direction of arrival estimationen_US
dc.typeArticleen_US

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