Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98517
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorNg, HCen_US
dc.creatorLiu, Sen_US
dc.creatorColeman, Ien_US
dc.creatorChu, RSWen_US
dc.creatorYue, MCen_US
dc.creatorLuk, Wen_US
dc.date.accessioned2023-05-10T02:00:01Z-
dc.date.available2023-05-10T02:00:01Z-
dc.identifier.isbn978-07-381051-8-5 (Electronic ISBN)en_US
dc.identifier.urihttp://hdl.handle.net/10397/98517-
dc.description2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers, Inc.en_US
dc.rightsThis work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.en_US
dc.rights© 2020 IEEE.en_US
dc.rightsThe following publication H. -C. Ng, S. Liu, I. Coleman, R. S. W. Chu, M. -C. Yue and W. Luk, "Acceleration of Short Read Alignment with Runtime Reconfiguration," 2020 International Conference on Field-Programmable Technology (ICFPT), Maui, HI, USA, 2020, pp. 256-262 is available at https://doi.org/10.1109/ICFPT51103.2020.00044.en_US
dc.titleAcceleration of short read alignment with runtime reconfigurationen_US
dc.typeConference Paperen_US
dc.identifier.spage256en_US
dc.identifier.epage262en_US
dc.identifier.doi10.1109/ICFPT51103.2020.00044en_US
dcterms.abstractRecent advancements in the throughput of next-generation sequencing machines pose a huge computational challenge in analyzing the massive quantities of sequenced data produced. A critical initial step of genomic data analysis is short read alignment, which is a bottleneck in the analysis workflow. This paper explores the use of a reconfigurable architecture to accelerate this process, based on the seed-and-extend model of Bowtie2. In the proposed approach, complete information available in sequencing data is integrated into an FPGA alignment pipeline for biologically accurate runtime acceleration. Experimental results show that our architecture achieves a similar alignment rate compared to Bowtie2, mapping reads around twice as fast. Particularly, the alignment time is reduced from 50 minutes to 26 minutes when processing 300M reads.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Proceedings : 2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020, p. 256-262. Washington, DC: IEEE, 2020en_US
dcterms.issued2020-
dc.identifier.scopus2-s2.0-85102083294-
dc.relation.ispartofbookProceedings : 2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020en_US
dc.relation.conferenceInternational Conference on Field-Programmable Technology [ICFPT]en_US
dc.description.validate202305 bcchen_US
dc.description.oaAuthor’s Originalen_US
dc.identifier.FolderNumberAMA-0107-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS54045864-
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