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- Publisher Website: 10.1109/ICFPT51103.2020.00044
- Scopus: eid_2-s2.0-85102083294
- WOS: WOS:000676387300035
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Conference Paper: Acceleration of Short Read Alignment with Runtime Reconfiguration
Title | Acceleration of Short Read Alignment with Runtime Reconfiguration |
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Authors | |
Issue Date | 2020 |
Citation | Proceedings - 2020 International Conference on Field-Programmable Technology, ICFPT 2020, 2020, p. 256-262 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/313631 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Ng, Ho Cheung | - |
dc.contributor.author | Liu, Shuanglong | - |
dc.contributor.author | Coleman, Izaak | - |
dc.contributor.author | Chu, Ringo S.W. | - |
dc.contributor.author | Yue, Man Chung | - |
dc.contributor.author | Luk, Wayne | - |
dc.date.accessioned | 2022-06-23T01:18:48Z | - |
dc.date.available | 2022-06-23T01:18:48Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Proceedings - 2020 International Conference on Field-Programmable Technology, ICFPT 2020, 2020, p. 256-262 | - |
dc.identifier.uri | http://hdl.handle.net/10722/313631 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings - 2020 International Conference on Field-Programmable Technology, ICFPT 2020 | - |
dc.title | Acceleration of Short Read Alignment with Runtime Reconfiguration | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICFPT51103.2020.00044 | - |
dc.identifier.scopus | eid_2-s2.0-85102083294 | - |
dc.identifier.spage | 256 | - |
dc.identifier.epage | 262 | - |
dc.identifier.isi | WOS:000676387300035 | - |