Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98517
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Ng, HC | en_US |
dc.creator | Liu, S | en_US |
dc.creator | Coleman, I | en_US |
dc.creator | Chu, RSW | en_US |
dc.creator | Yue, MC | en_US |
dc.creator | Luk, W | en_US |
dc.date.accessioned | 2023-05-10T02:00:01Z | - |
dc.date.available | 2023-05-10T02:00:01Z | - |
dc.identifier.isbn | 978-07-381051-8-5 (Electronic ISBN) | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/98517 | - |
dc.description | 2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020 | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers, Inc. | en_US |
dc.rights | This 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.rights | The 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.title | Acceleration of short read alignment with runtime reconfiguration | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 256 | en_US |
dc.identifier.epage | 262 | en_US |
dc.identifier.doi | 10.1109/ICFPT51103.2020.00044 | en_US |
dcterms.abstract | Recent 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.accessRights | open access | en_US |
dcterms.bibliographicCitation | In Proceedings : 2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020, p. 256-262. Washington, DC: IEEE, 2020 | en_US |
dcterms.issued | 2020 | - |
dc.identifier.scopus | 2-s2.0-85102083294 | - |
dc.relation.ispartofbook | Proceedings : 2020 International Conference on Field-Programmable Technology, ICFPT 2020, Maui, HI, USA, 7-8 December 2020 | en_US |
dc.relation.conference | International Conference on Field-Programmable Technology [ICFPT] | en_US |
dc.description.validate | 202305 bcch | en_US |
dc.description.oa | Author’s Original | en_US |
dc.identifier.FolderNumber | AMA-0107 | - |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 54045864 | - |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Yue_Acceleration_Short_Read.pdf | Preprint Version | 1.13 MB | Adobe PDF | View/Open |
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