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dc.contributor.author
Kim, Jeremie S.
dc.contributor.author
Cali, Damla S.
dc.contributor.author
Xin, Hongyi
dc.contributor.author
Lee, Donghyuk
dc.contributor.author
Ghose, Saugata
dc.contributor.author
Alser, Mohammed
dc.contributor.author
Hassan, Hasan
dc.contributor.author
Ergin, Oğuz
dc.contributor.author
Alkan, Can
dc.contributor.author
Mutlu, Onur
dc.date.accessioned
2021-10-08T07:04:05Z
dc.date.available
2018-05-23T04:48:57Z
dc.date.available
2018-05-24T13:39:07Z
dc.date.available
2021-10-08T07:04:05Z
dc.date.issued
2018
dc.identifier.issn
1471-2164
dc.identifier.other
10.1186/s12864-018-4460-0
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/265528
dc.identifier.doi
10.3929/ethz-b-000265528
dc.description.abstract
Background Seed location filtering is critical in DNA read mapping, a process where billions of DNA fragments (reads) sampled from a donor are mapped onto a reference genome to identify genomic variants of the donor. State-of-the-art read mappers 1) quickly generate possible mapping locations for seeds (i.e., smaller segments) within each read, 2) extract reference sequences at each of the mapping locations, and 3) check similarity between each read and its associated reference sequences with a computationally-expensive algorithm (i.e., sequence alignment) to determine the origin of the read. A seed location filter comes into play before alignment, discarding seed locations that alignment would deem a poor match. The ideal seed location filter would discard all poor match locations prior to alignment such that there is no wasted computation on unnecessary alignments. Results We propose a novel seed location filtering algorithm, GRIM-Filter, optimized to exploit 3D-stacked memory systems that integrate computation within a logic layer stacked under memory layers, to perform processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1) introducing a new representation of coarse-grained segments of the reference genome, and 2) using massively-parallel in-memory operations to identify read presence within each coarse-grained segment. Our evaluations show that for a sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false negative rate of filtering by 5.59x–6.41x, and 2) provides an end-to-end read mapper speedup of 1.81x–3.65x, compared to a state-of-the-art read mapper employing the best previous seed location filtering algorithm. Conclusion GRIM-Filter exploits 3D-stacked memory, which enables the efficient use of processing-in-memory, to overcome the memory bandwidth bottleneck in seed location filtering. We show that GRIM-Filter significantly improves the performance of a state-of-the-art read mapper. GRIM-Filter is a universal seed location filter that can be applied to any read mapper. We hope that our results provide inspiration for new works to design other bioinformatics algorithms that take advantage of emerging technologies and new processing paradigms, such as processing-in-memory using 3D-stacked memory devices.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
High throughput sequencing
en_US
dc.subject
Genome sequencing
en_US
dc.subject
Seed location filtering
en_US
dc.subject
3D-stacked DRAM
en_US
dc.subject
Processing-in-memory
en_US
dc.subject
Emerging memory technologies
en_US
dc.title
GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2018-05-09
ethz.journal.title
BMC Genomics
ethz.journal.volume
19
en_US
ethz.journal.issue
S2
en_US
ethz.journal.abbreviated
BMC Genomics
ethz.pages.start
89
en_US
ethz.size
18 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.event
16th Asia Pacific Bioinformatics Conference (APBC 2018) - Genomics
en_US
ethz.event.location
Yokohama, Japan
en_US
ethz.event.date
January 15-17, 2018
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02158 - IT Services Gruppe (ISG) D-INFK / IT Services Group (ISG) D-INFK
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::09483 - Mutlu, Onur / Mutlu, Onur
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::09483 - Mutlu, Onur / Mutlu, Onur
ethz.date.deposited
2018-05-23T04:49:45Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-05-24T13:39:16Z
ethz.rosetta.lastUpdated
2024-02-02T15:03:42Z
ethz.rosetta.versionExported
true
ethz.COinS
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