Towards hardware-driven design of low-energy algorithms for data analysis

dc.contributor.authorIndre Zliobaite
dc.contributor.authorJaakko Hollmen
dc.contributor.authorJukka Teittinen
dc.contributor.authorLauri Koskinen
dc.contributor.organizationfi=Technology Research Center TRC|en=Technology Research Center TRC|
dc.contributor.organization-code1.2.246.10.2458963.20.58905910210
dc.contributor.organization-code2609060
dc.converis.publication-id3018226
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/3018226
dc.date.accessioned2022-10-27T12:09:45Z
dc.date.available2022-10-27T12:09:45Z
dc.description.abstract<p> In the era of &quot;big&quot; data, data analysis algorithms need to be efficient. Traditionally researchers would tackle this problem by considering &quot;small&quot; data algorithms, and investigating how to make them computationally more efficient for big data applications. The main means to achieve computational efficiency would be to revise the necessity and order of subroutines, or to approximate calculations. This paper presents a viewpoint that in order to be able to cope with the new challenges of the growing digital universe, research needs to take a combined view towards data analysis algorithm design and hardware design, and discusses a potential research direction in taking an intreated approach in terms of algorithm design and hardware design. Analyzing how data mining algorithms operate at the elementary operations level can help do design more specialized and dedicated hardware, that, for instance, would be more energy efficient. In turn, understanding hardware design can help to develop more effective algorithms.</p>
dc.format.pagerange15
dc.format.pagerange20
dc.identifier.eissn1943-5835
dc.identifier.jour-issn0163-5808
dc.identifier.olddbid173609
dc.identifier.oldhandle10024/156703
dc.identifier.urihttps://www.utupub.fi/handle/11111/32726
dc.identifier.urnURN:NBN:fi-fe2021042714974
dc.language.isoen
dc.okm.affiliatedauthorTeittinen, Jukka
dc.okm.affiliatedauthorKoskinen, Lauri
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline213 Electronic, automation and communications engineering, electronicsen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline213 Sähkö-, automaatio- ja tietoliikennetekniikka, elektroniikkafi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherA C M Special Interest Group
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.doi10.1145/2737817.2737821
dc.relation.ispartofjournalSigmod Record
dc.relation.issue4
dc.relation.volume43
dc.source.identifierhttps://www.utupub.fi/handle/10024/156703
dc.titleTowards hardware-driven design of low-energy algorithms for data analysis
dc.year.issued2014

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