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Using statistical analysis to fine-tune the results of knapsack-based computational platform benchmarking

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dc.contributor.authorNatalia, K.
dc.contributor.authorMikhail, K.
dc.contributor.authorGeorgii, B.
dc.contributor.authorКуприяшин, Михаил Андреевич
dc.contributor.authorБорзунов, Георгий Иванович
dc.date.accessioned2024-11-20T10:35:10Z
dc.date.available2024-11-20T10:35:10Z
dc.date.issued2019
dc.description.abstract© 2019 IEEE In previous papers, we composed an algorithmic foundation for computational platform benchmarking of well-known exact algorithms for the Knapsack Problem. We suggested using the run time of these algorithms with fixed inputs as the performance estimates. We then derived a single performance estimate, equally impacted by each of the algorithms. Although this approach makes for a reasonable general-purpose benchmark, equalizing the impact of different algorithms is not completely legitimate, as they have different processing requirements. In this paper, we perform an in-depth analysis of algorithm operational requirements and try to fine-tune the integral estimates to describe special-purpose (e.g. data compression or encipherment/decipherment) platforms more accurately.
dc.format.extentС. 1816-1820
dc.identifier.citationNatalia, K. Using statistical analysis to fine-tune the results of knapsack-based computational platform benchmarking / Natalia, K., Mikhail, K., Georgii, B. // Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019. - 2019. - P. 1816-1820. - 10.1109/EIConRus.2019.8657218
dc.identifier.doi10.1109/EIConRus.2019.8657218
dc.identifier.urihttps://www.doi.org/10.1109/EIConRus.2019.8657218
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85063468760&origin=resultslist
dc.identifier.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000469452600423
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/16753
dc.relation.ispartofProceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019
dc.titleUsing statistical analysis to fine-tune the results of knapsack-based computational platform benchmarking
dc.typeConference Paper
dspace.entity.typePublication
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