Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment

Dariusz Rafal Augustyn; Lukasz Warchal

doi:10.1007/978-3-319-01863-8_24

Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment

Dariusz Rafal Augustyn
, Lukasz Warchal

Katedra Informatyki Stosowanej (RAU/RAU7)

Silesian University of Technology

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

Abstrakt

Query selectivity is a parameter that allows to estimate the size of data satisfying a query condition. For complex range query condition it may be defined as multi integral over a multivariate probability density function (PDF). It describes a multidimensional attribute value distribution and may be estimated using the known approach based on a superposition of Gaussian clusters. But there is the problem of an efficient integration of the multivariate PDF. This may be solved by applying Monte Carlo (MC) method which exposes its advantages for high dimensions. To satisfy the time constraint of selectivity calculation, the parallelized MC integration method was proposed in the paper. The implementation of the method is based on CUDA technology. The paper also describes the application designated for obtaining the time-optimal parameter values of the method.

Język oryginału	angielski
Tytuł publikacji goszczącej	New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events
Redaktorzy	Tania Cerquitelli, Silvia Chiusano, Athena Vakali, Boris Novikov, Jaroslav Pokorný, Barbara Catania, Giovanna Guerrini, Alfons Kemper, Themis Palpanas, Mirko Kämpf
Wydawca	Springer Verlag
Strony	215-224
Liczba stron	10
ISBN (elektroniczny)	9783319018621
Identyfikatory DOI	https://doi.org/10.1007/978-3-319-01863-8_24
Status publikacji	Opublikowano - 2014
Wydarzenie	17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013 - Genoa, Włochy Czas trwania: 1 wrz 2013 → 4 wrz 2013

Seria publikacji

Nazwa	Advances in Intelligent Systems and Computing
Tom	241
ISSN (drukowany)	2194-5357

Konferencja

Konferencja	17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013
Kraj/Terytorium	Włochy
Miejscowość	Genoa
Okres	1/09/13 → 4/09/13

Obszary tematyczne ASJC Scopus

Inżynieria sterowania i systemów
Informatyka ogólna

Uzyskaj dostęp do dokumentu

10.1007/978-3-319-01863-8_24

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Augustyn, D. R., & Warchal, L. (2014). Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment. W T. Cerquitelli, S. Chiusano, A. Vakali, B. Novikov, J. Pokorný, B. Catania, G. Guerrini, A. Kemper, T. Palpanas, & M. Kämpf (Red.), New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events (str. 215-224). (Advances in Intelligent Systems and Computing; Tom 241). Springer Verlag. https://doi.org/10.1007/978-3-319-01863-8_24

Augustyn, Dariusz Rafal ; Warchal, Lukasz. / Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment. New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events. redaktor / Tania Cerquitelli ; Silvia Chiusano ; Athena Vakali ; Boris Novikov ; Jaroslav Pokorný ; Barbara Catania ; Giovanna Guerrini ; Alfons Kemper ; Themis Palpanas ; Mirko Kämpf. Springer Verlag, 2014. str. 215-224 (Advances in Intelligent Systems and Computing).

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title = "Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment",

abstract = "Query selectivity is a parameter that allows to estimate the size of data satisfying a query condition. For complex range query condition it may be defined as multi integral over a multivariate probability density function (PDF). It describes a multidimensional attribute value distribution and may be estimated using the known approach based on a superposition of Gaussian clusters. But there is the problem of an efficient integration of the multivariate PDF. This may be solved by applying Monte Carlo (MC) method which exposes its advantages for high dimensions. To satisfy the time constraint of selectivity calculation, the parallelized MC integration method was proposed in the paper. The implementation of the method is based on CUDA technology. The paper also describes the application designated for obtaining the time-optimal parameter values of the method.",

keywords = "CUDA, Data clustering, Monte carlo integration, Selectivity estimation",

author = "Augustyn, \{Dariusz Rafal\} and Lukasz Warchal",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013 ; Conference date: 01-09-2013 Through 04-09-2013",

year = "2014",

doi = "10.1007/978-3-319-01863-8\_24",

language = "English",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "215--224",

editor = "Tania Cerquitelli and Silvia Chiusano and Athena Vakali and Boris Novikov and Jaroslav Pokorn{\'y} and Barbara Catania and Giovanna Guerrini and Alfons Kemper and Themis Palpanas and Mirko K{\"a}mpf",

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Augustyn, DR & Warchal, L 2014, Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment. w T Cerquitelli, S Chiusano, A Vakali, B Novikov, J Pokorný, B Catania, G Guerrini, A Kemper, T Palpanas & M Kämpf (red), New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events. Advances in Intelligent Systems and Computing, tom 241, Springer Verlag, str. 215-224, 17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013, Genoa, Włochy, 1/09/13. https://doi.org/10.1007/978-3-319-01863-8_24

Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment. / Augustyn, Dariusz Rafal; Warchal, Lukasz.
New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events. red. / Tania Cerquitelli; Silvia Chiusano; Athena Vakali; Boris Novikov; Jaroslav Pokorný; Barbara Catania; Giovanna Guerrini; Alfons Kemper; Themis Palpanas; Mirko Kämpf. Springer Verlag, 2014. str. 215-224 (Advances in Intelligent Systems and Computing; Tom 241).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment

AU - Augustyn, Dariusz Rafal

AU - Warchal, Lukasz

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2014.

PY - 2014

Y1 - 2014

N2 - Query selectivity is a parameter that allows to estimate the size of data satisfying a query condition. For complex range query condition it may be defined as multi integral over a multivariate probability density function (PDF). It describes a multidimensional attribute value distribution and may be estimated using the known approach based on a superposition of Gaussian clusters. But there is the problem of an efficient integration of the multivariate PDF. This may be solved by applying Monte Carlo (MC) method which exposes its advantages for high dimensions. To satisfy the time constraint of selectivity calculation, the parallelized MC integration method was proposed in the paper. The implementation of the method is based on CUDA technology. The paper also describes the application designated for obtaining the time-optimal parameter values of the method.

AB - Query selectivity is a parameter that allows to estimate the size of data satisfying a query condition. For complex range query condition it may be defined as multi integral over a multivariate probability density function (PDF). It describes a multidimensional attribute value distribution and may be estimated using the known approach based on a superposition of Gaussian clusters. But there is the problem of an efficient integration of the multivariate PDF. This may be solved by applying Monte Carlo (MC) method which exposes its advantages for high dimensions. To satisfy the time constraint of selectivity calculation, the parallelized MC integration method was proposed in the paper. The implementation of the method is based on CUDA technology. The paper also describes the application designated for obtaining the time-optimal parameter values of the method.

KW - CUDA

KW - Data clustering

KW - Monte carlo integration

KW - Selectivity estimation

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DO - 10.1007/978-3-319-01863-8_24

M3 - Conference contribution

AN - SCOPUS:84927511429

T3 - Advances in Intelligent Systems and Computing

SP - 215

EP - 224

BT - New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events

A2 - Cerquitelli, Tania

A2 - Chiusano, Silvia

A2 - Vakali, Athena

A2 - Novikov, Boris

A2 - Pokorný, Jaroslav

A2 - Catania, Barbara

A2 - Guerrini, Giovanna

A2 - Kemper, Alfons

A2 - Palpanas, Themis

A2 - Kämpf, Mirko

PB - Springer Verlag

T2 - 17th East European Conference on Advances in Databases and Information Systems, ADBIS 2013

Y2 - 1 September 2013 through 4 September 2013

ER -

Augustyn DR, Warchal L. Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment. W Cerquitelli T, Chiusano S, Vakali A, Novikov B, Pokorný J, Catania B, Guerrini G, Kemper A, Palpanas T, Kämpf M, redaktorzy, New Trends in Databases and Information Systems - Selected Papers of the 17th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events. Springer Verlag. 2014. str. 215-224. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-01863-8_24

Gpu-accelerated query selectivity estimation based on data clustering and monte carlo integration method developed in cuda environment

Abstrakt

Seria publikacji

Konferencja

Obszary tematyczne ASJC Scopus

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Inne pliki i linki

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