Show simple item record

dc.contributor.authorHussain, H. M.en
dc.contributor.authorBenkrid, K.en
dc.contributor.authorSeker, H.en
dc.date.accessioned2014-09-08T10:11:09Z
dc.date.available2014-09-08T10:11:09Z
dc.date.issued2013
dc.identifier.citationHussain, H.M., Benkrid, K. & Seker, H. (2013) Reconfiguration-based implementation of SVM classifier on FPGA for classifying microarray data. Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE, pp. 3058-3061.en
dc.identifier.issn1557-170X
dc.identifier.urihttp://hdl.handle.net/2086/10229
dc.description.abstractClassifying Microarray data, which are of high dimensional nature, requires high computational power. Support Vector Machines-based classifier (SVM) is among the most common and successful classifiers used in the analysis of Microarray data but also requires high computational power due to its complex mathematical architecture. Implementing SVM on hardware exploits the parallelism available within the algorithm kernels to accelerate the classification of Microarray data. In this work, a flexible, dynamically and partially reconfigurable implementation of the SVM classifier on Field Programmable Gate Array (FPGA) is presented. The SVM architecture achieved up to 85× speed-up over equivalent general purpose processor (GPP) showing the capability of FPGAs in enhancing the performance of SVM-based analysis of Microarray data as well as future bioinformatics applications.en
dc.language.isoenen
dc.publisherIEEEen
dc.subjectBioinformaticsen
dc.titleReconfiguration-based implementation of SVM classifier on FPGA for classifying microarray data.en
dc.typeConferenceen
dc.identifier.doihttp://dx.doi.org/10.1109/EMBC.2013.6610186
dc.funderN/Aen
dc.projectidN/Aen


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record