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GPU parallel implementation of the approximate K-SVD algorithm using OpenCL

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Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO)
KustantajaEuropean Signal Processing Conference, EUSIPCO
Sivut271-275
Sivumäärä5
ISBN (painettu)9780992862619
TilaJulkaistu - 10 marraskuuta 2014
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaEUROPEAN SIGNAL PROCESSING CONFERENCE -
Kesto: 1 tammikuuta 1900 → …

Conference

ConferenceEUROPEAN SIGNAL PROCESSING CONFERENCE
Ajanjakso1/01/00 → …

Tiivistelmä

Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. We investigate a parallel version of the approximate K-SVD algorithm, where multiple atoms are updated simultaneously, and implement it using OpenCL, for execution on graphics processing units (GPU). This not only allows reducing the execution time with respect to the standard sequential version, but also gives dictionaries with which the training data are better approximated. We present numerical evidence supporting this somewhat surprising conclusion and discuss in detail several implementation choices and difficulties.

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