HISPANA | Directorio nacional de recursos digitales > Datos do registro

Está en:  › Datos do registro

Linked Open Data

A gpu-based implementation for range queries on spaghettis data structure

Identificadores del recurso

Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629

978-3-642-21927-6

0302-9743

http://hdl.handle.net/10578/1773

Procedencia

(RUIdeRA : Repositorio Universitario Institucional de Recursos Abiertos)

Ficha

Título:: A gpu-based implementation for range queries on spaghettis data structure
Tema:: Ciencias de la computación y tecnología informática
Descrición:: Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA
Idioma:
Autor/Productor:: Uribe Paredes, Roberto; Sanchez Garcia, Jose Luis; Cazorla Lopez, Diego C.; Valero Lara, Pedro; Arias Antunez, Enrique
Editor:: Springer-Verlag
Dereitos:: info:eu-repo/semantics/openAccess
Data:: 2012-01-13T07:10:17Z; 2011
Tipo de recurso:: info:eu-repo/semantics/article
Formato:: text/plain

oai_dc

<?xml version="1.0" encoding="UTF-8" ?>

<oai_dc:dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
1. <dc:title>A gpu-based implementation for range queries on spaghettis data structure</dc:title>
2. <dc:creator>Uribe Paredes, Roberto</dc:creator>
3. <dc:creator>Sanchez Garcia, Jose Luis</dc:creator>
4. <dc:creator>Cazorla Lopez, Diego C.</dc:creator>
5. <dc:creator>Valero Lara, Pedro</dc:creator>
6. <dc:creator>Arias Antunez, Enrique</dc:creator>
7. <dc:subject>Ciencias de la computación y tecnología informática</dc:subject>
8. <dc:description>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</dc:description>
9. <dc:date>2012-01-13T07:10:17Z</dc:date>
10. <dc:date>2012-01-13T07:10:17Z</dc:date>
11. <dc:date>2011</dc:date>
12. <dc:type>info:eu-repo/semantics/article</dc:type>
13. <dc:identifier>Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</dc:identifier>
14. <dc:identifier>978-3-642-21927-6</dc:identifier>
15. <dc:identifier>0302-9743</dc:identifier>
16. <dc:identifier>http://hdl.handle.net/10578/1773</dc:identifier>
17. <dc:language>es</dc:language>
18. <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
19. <dc:format>text/plain</dc:format>
20. <dc:publisher>Springer-Verlag</dc:publisher>
</oai_dc:dc>

didl

<?xml version="1.0" encoding="UTF-8" ?>

<d:DIDL schemaLocation="urn:mpeg:mpeg21:2002:02-DIDL-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/did/didl.xsd">
1. <d:DIDLInfo>
  1. <dcterms:created schemaLocation="http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/dcterms.xsd">2012-01-13T07:10:17Z</dcterms:created>
  </d:DIDLInfo>
2. <d:Item id="hdl_10578_1773">
  1. <d:Descriptor>
    1. <d:Statement mimeType="application/xml; charset=utf-8">
      1. <dii:Identifier schemaLocation="urn:mpeg:mpeg21:2002:01-DII-NS http://standards.iso.org/ittf/PubliclyAvailableStandards/MPEG-21_schema_files/dii/dii.xsd">urn:hdl:10578/1773</dii:Identifier>
      </d:Statement>
    </d:Descriptor>
  2. <d:Descriptor>
    1. <d:Statement mimeType="application/xml; charset=utf-8">
      1. <oai_dc:dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
        <dc:title>A gpu-based implementation for range queries on spaghettis data structure</dc:title>
        <dc:creator>Uribe Paredes, Roberto</dc:creator>
        <dc:creator>Sanchez Garcia, Jose Luis</dc:creator>
        <dc:creator>Cazorla Lopez, Diego C.</dc:creator>
        <dc:creator>Valero Lara, Pedro</dc:creator>
        <dc:creator>Arias Antunez, Enrique</dc:creator>
        <dc:subject>Ciencias de la computación y tecnología informática</dc:subject>
        <dc:description>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</dc:description>
        <dc:date>2012-01-13T07:10:17Z</dc:date>
        <dc:date>2012-01-13T07:10:17Z</dc:date>
        <dc:date>2011</dc:date>
        <dc:type>info:eu-repo/semantics/article</dc:type>
        <dc:identifier>Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</dc:identifier>
        <dc:identifier>978-3-642-21927-6</dc:identifier>
        <dc:identifier>0302-9743</dc:identifier>
        <dc:identifier>http://hdl.handle.net/10578/1773</dc:identifier>
        <dc:language>es</dc:language>
        <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
        <dc:publisher>Springer-Verlag</dc:publisher>
        </oai_dc:dc>
      </d:Statement>
    </d:Descriptor>
  3. <d:Component id="10578_1773_1">
    1. <d:Resource mimeType="application/pdf" ref="http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf" />
    </d:Component>
  </d:Item>
</d:DIDL>

dim

<?xml version="1.0" encoding="UTF-8" ?>

<dim:dim schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
1. <dim:field element="contributor" lang="es_ES" mdschema="dc" qualifier="author">Uribe Paredes, Roberto</dim:field>
2. <dim:field element="contributor" lang="es_ES" mdschema="dc" qualifier="author">Sanchez Garcia, Jose Luis</dim:field>
3. <dim:field element="contributor" lang="es_ES" mdschema="dc" qualifier="author">Cazorla Lopez, Diego C.</dim:field>
4. <dim:field element="contributor" lang="es_ES" mdschema="dc" qualifier="author">Valero Lara, Pedro</dim:field>
5. <dim:field element="contributor" lang="es_ES" mdschema="dc" qualifier="author">Arias Antunez, Enrique</dim:field>
6. <dim:field element="date" mdschema="dc" qualifier="accessioned">2012-01-13T07:10:17Z</dim:field>
7. <dim:field element="date" mdschema="dc" qualifier="available">2012-01-13T07:10:17Z</dim:field>
8. <dim:field element="date" lang="es_ES" mdschema="dc" qualifier="issued">2011</dim:field>
9. <dim:field element="identifier" lang="es_ES" mdschema="dc" qualifier="citation">Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</dim:field>
10. <dim:field element="identifier" lang="es_ES" mdschema="dc" qualifier="isbn">978-3-642-21927-6</dim:field>
11. <dim:field element="identifier" lang="es_ES" mdschema="dc" qualifier="issn">0302-9743</dim:field>
12. <dim:field element="identifier" mdschema="dc" qualifier="uri">http://hdl.handle.net/10578/1773</dim:field>
13. <dim:field element="description" lang="es_ES" mdschema="dc" qualifier="abstract">Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</dim:field>
14. <dim:field element="format" lang="en_US" mdschema="dc">text/plain</dim:field>
15. <dim:field element="language" lang="en_US" mdschema="dc" qualifier="iso">es</dim:field>
16. <dim:field element="publisher" lang="es_ES" mdschema="dc">Springer-Verlag</dim:field>
17. <dim:field element="rights" lang="en_US" mdschema="dc">info:eu-repo/semantics/openAccess</dim:field>
18. <dim:field element="subject" lang="es_ES" mdschema="dc">Ciencias de la computación y tecnología informática</dim:field>
19. <dim:field element="title" lang="es_ES" mdschema="dc">A gpu-based implementation for range queries on spaghettis data structure</dim:field>
20. <dim:field element="type" lang="en_US" mdschema="dc">info:eu-repo/semantics/article</dim:field>
</dim:dim>

etdms

<?xml version="1.0" encoding="UTF-8" ?>

<thesis schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.0/ http://www.ndltd.org/standards/metadata/etdms/1.0/etdms.xsd">
1. <title>A gpu-based implementation for range queries on spaghettis data structure</title>
2. <creator>Uribe Paredes, Roberto</creator>
3. <creator>Sanchez Garcia, Jose Luis</creator>
4. <creator>Cazorla Lopez, Diego C.</creator>
5. <creator>Valero Lara, Pedro</creator>
6. <creator>Arias Antunez, Enrique</creator>
7. <subject>Ciencias de la computación y tecnología informática</subject>
8. <description>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</description>
9. <date>2012-01-13</date>
10. <date>2012-01-13</date>
11. <date>2011</date>
12. <type>info:eu-repo/semantics/article</type>
13. <identifier>Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</identifier>
14. <identifier>978-3-642-21927-6</identifier>
15. <identifier>0302-9743</identifier>
16. <identifier>http://hdl.handle.net/10578/1773</identifier>
17. <language>es</language>
18. <rights>info:eu-repo/semantics/openAccess</rights>
19. <publisher>Springer-Verlag</publisher>
</thesis>

marc

<?xml version="1.0" encoding="UTF-8" ?>

<record schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
1. <leader>00925njm 22002777a 4500</leader>
2. <datafield ind1=" " ind2=" " tag="042">
  1. <subfield code="a">dc</subfield>
  </datafield>
3. <datafield ind1=" " ind2=" " tag="720">
  1. <subfield code="a">Uribe Paredes, Roberto</subfield>
  2. <subfield code="e">author</subfield>
  </datafield>
4. <datafield ind1=" " ind2=" " tag="720">
  1. <subfield code="a">Sanchez Garcia, Jose Luis</subfield>
  2. <subfield code="e">author</subfield>
  </datafield>
5. <datafield ind1=" " ind2=" " tag="720">
  1. <subfield code="a">Cazorla Lopez, Diego C.</subfield>
  2. <subfield code="e">author</subfield>
  </datafield>
6. <datafield ind1=" " ind2=" " tag="720">
  1. <subfield code="a">Valero Lara, Pedro</subfield>
  2. <subfield code="e">author</subfield>
  </datafield>
7. <datafield ind1=" " ind2=" " tag="720">
  1. <subfield code="a">Arias Antunez, Enrique</subfield>
  2. <subfield code="e">author</subfield>
  </datafield>
8. <datafield ind1=" " ind2=" " tag="260">
  1. <subfield code="c">2011</subfield>
  </datafield>
9. <datafield ind1=" " ind2=" " tag="520">
  1. <subfield code="a">Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</subfield>
  </datafield>
10. <datafield ind1="8" ind2=" " tag="024">
  1. <subfield code="a">Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</subfield>
  </datafield>
11. <datafield ind1="8" ind2=" " tag="024">
  1. <subfield code="a">978-3-642-21927-6</subfield>
  </datafield>
12. <datafield ind1="8" ind2=" " tag="024">
  1. <subfield code="a">0302-9743</subfield>
  </datafield>
13. <datafield ind1="8" ind2=" " tag="024">
  1. <subfield code="a">http://hdl.handle.net/10578/1773</subfield>
  </datafield>
14. <datafield ind1=" " ind2=" " tag="653">
  1. <subfield code="a">Ciencias de la computación y tecnología informática</subfield>
  </datafield>
15. <datafield ind1="0" ind2="0" tag="245">
  1. <subfield code="a">A gpu-based implementation for range queries on spaghettis data structure</subfield>
  </datafield>
</record>

mets

<?xml version="1.0" encoding="UTF-8" ?>

<mets ID=" DSpace_ITEM_10578-1773" OBJID=" hdl:10578/1773" PROFILE="DSpace METS SIP Profile 1.0" TYPE="DSpace ITEM" schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd">
1. <metsHdr CREATEDATE="2016-09-23T21:46:25Z">
  1. <agent ROLE="CUSTODIAN" TYPE="ORGANIZATION">
    1. <name>Ruidera UCLM</name>
    </agent>
  </metsHdr>
2. <dmdSec ID="DMD_10578_1773">
  1. <mdWrap MDTYPE="MODS">
    1. <xmlData schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
      1. <mods:mods schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
        <mods:name>
        <mods:role>
        <mods:roleTerm type="text">author</mods:roleTerm>
        </mods:role>
        <mods:namePart>Uribe Paredes, Roberto</mods:namePart>
        </mods:name>
        <mods:name>
        <mods:role>
        <mods:roleTerm type="text">author</mods:roleTerm>
        </mods:role>
        <mods:namePart>Sanchez Garcia, Jose Luis</mods:namePart>
        </mods:name>
        <mods:name>
        <mods:role>
        <mods:roleTerm type="text">author</mods:roleTerm>
        </mods:role>
        <mods:namePart>Cazorla Lopez, Diego C.</mods:namePart>
        </mods:name>
        <mods:name>
        <mods:role>
        <mods:roleTerm type="text">author</mods:roleTerm>
        </mods:role>
        <mods:namePart>Valero Lara, Pedro</mods:namePart>
        </mods:name>
        <mods:name>
        <mods:role>
        <mods:roleTerm type="text">author</mods:roleTerm>
        </mods:role>
        <mods:namePart>Arias Antunez, Enrique</mods:namePart>
        </mods:name>
        <mods:extension>
        <mods:dateAccessioned encoding="iso8601">2012-01-13T07:10:17Z</mods:dateAccessioned>
        </mods:extension>
        <mods:extension>
        <mods:dateAvailable encoding="iso8601" />
        </mods:extension>
        <mods:originInfo>
        <mods:dateIssued encoding="iso8601">2011</mods:dateIssued>
        </mods:originInfo>
        <mods:identifier type="citation">Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</mods:identifier>
        <mods:identifier type="isbn">978-3-642-21927-6</mods:identifier>
        <mods:identifier type="issn">0302-9743</mods:identifier>
        <mods:identifier type="uri">http://hdl.handle.net/10578/1773</mods:identifier>
        <mods:abstract>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</mods:abstract>
        <mods:language>
        <mods:languageTerm authority="rfc3066">es</mods:languageTerm>
        </mods:language>
        <mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
        <mods:subject>
        <mods:topic>Ciencias de la computación y tecnología informática</mods:topic>
        </mods:subject>
        <mods:titleInfo>
        <mods:title>A gpu-based implementation for range queries on spaghettis data structure</mods:title>
        </mods:titleInfo>
        <mods:genre>info:eu-repo/semantics/article</mods:genre>
        </mods:mods>
      </xmlData>
    </mdWrap>
  </dmdSec>
3. <amdSec ID="TMD_10578_1773">
  1. <rightsMD ID="RIG_10578_1773">
    1. <mdWrap MDTYPE="OTHER" MIMETYPE="text/plain" OTHERMDTYPE="DSpaceDepositLicense">
      1. <binData>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</binData>
      </mdWrap>
    </rightsMD>
  </amdSec>
4. <amdSec ID="FO_10578_1773_1">
  1. <techMD ID="TECH_O_10578_1773_1">
    1. <mdWrap MDTYPE="PREMIS">
      1. <xmlData schemaLocation="http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd">
        <premis:premis>
        <premis:object>
        <premis:objectIdentifier>
        <premis:objectIdentifierType>URL</premis:objectIdentifierType>
        <premis:objectIdentifierValue>http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf</premis:objectIdentifierValue>
        </premis:objectIdentifier>
        <premis:objectCategory>File</premis:objectCategory>
        <premis:objectCharacteristics>
        <premis:fixity>
        <premis:messageDigestAlgorithm>MD5</premis:messageDigestAlgorithm>
        <premis:messageDigest>5b6f1f461060343241dd20cd343b88ed</premis:messageDigest>
        </premis:fixity>
        <premis:size>166953</premis:size>
        <premis:format>
        <premis:formatDesignation>
        <premis:formatName>application/pdf</premis:formatName>
        </premis:formatDesignation>
        </premis:format>
        </premis:objectCharacteristics>
        <premis:originalName>fi_1320857362-ruribeiccsa2011cameraready.pdf</premis:originalName>
        </premis:object>
        </premis:premis>
        </xmlData>
      </mdWrap>
    </techMD>
  </amdSec>
5. <amdSec ID="FT_10578_1773_3">
  1. <techMD ID="TECH_T_10578_1773_3">
    1. <mdWrap MDTYPE="PREMIS">
      1. <xmlData schemaLocation="http://www.loc.gov/standards/premis http://www.loc.gov/standards/premis/PREMIS-v1-0.xsd">
        <premis:premis>
        <premis:object>
        <premis:objectIdentifier>
        <premis:objectIdentifierType>URL</premis:objectIdentifierType>
        <premis:objectIdentifierValue>http://localhost:8080/xmlui/bitstream/10578/1773/3/fi_1320857362-ruribeiccsa2011cameraready.pdf.txt</premis:objectIdentifierValue>
        </premis:objectIdentifier>
        <premis:objectCategory>File</premis:objectCategory>
        <premis:objectCharacteristics>
        <premis:fixity>
        <premis:messageDigestAlgorithm>MD5</premis:messageDigestAlgorithm>
        <premis:messageDigest>16ebaf2dcc971a3eea8afb9ead91e507</premis:messageDigest>
        </premis:fixity>
        <premis:size>35290</premis:size>
        <premis:format>
        <premis:formatDesignation>
        <premis:formatName>text/plain</premis:formatName>
        </premis:formatDesignation>
        </premis:format>
        </premis:objectCharacteristics>
        <premis:originalName>fi_1320857362-ruribeiccsa2011cameraready.pdf.txt</premis:originalName>
        </premis:object>
        </premis:premis>
        </xmlData>
      </mdWrap>
    </techMD>
  </amdSec>
6. <fileSec>
  1. <fileGrp USE="ORIGINAL">
    1. <file ADMID="FO_10578_1773_1" CHECKSUM="5b6f1f461060343241dd20cd343b88ed" CHECKSUMTYPE="MD5" GROUPID="GROUP_BITSTREAM_10578_1773_1" ID="BITSTREAM_ORIGINAL_10578_1773_1" MIMETYPE="application/pdf" SEQ="1" SIZE="166953">
      1. <FLocat LOCTYPE="URL" href="http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf" type="simple" />
      </file>
    </fileGrp>
  2. <fileGrp USE="TEXT">
    1. <file ADMID="FT_10578_1773_3" CHECKSUM="16ebaf2dcc971a3eea8afb9ead91e507" CHECKSUMTYPE="MD5" GROUPID="GROUP_BITSTREAM_10578_1773_3" ID="BITSTREAM_TEXT_10578_1773_3" MIMETYPE="text/plain" SEQ="3" SIZE="35290">
      1. <FLocat LOCTYPE="URL" href="http://localhost:8080/xmlui/bitstream/10578/1773/3/fi_1320857362-ruribeiccsa2011cameraready.pdf.txt" type="simple" />
      </file>
    </fileGrp>
  </fileSec>
7. <structMap LABEL="DSpace Object" TYPE="LOGICAL">
  1. <div ADMID="DMD_10578_1773" TYPE="DSpace Object Contents">
    1. <div TYPE="DSpace BITSTREAM">
      1. <fptr FILEID="BITSTREAM_ORIGINAL_10578_1773_1" />
      </div>
    </div>
  </structMap>
</mets>

mods

<?xml version="1.0" encoding="UTF-8" ?>

<mods:mods schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
1. <mods:name>
  1. <mods:namePart>Uribe Paredes, Roberto</mods:namePart>
  </mods:name>
2. <mods:name>
  1. <mods:namePart>Sanchez Garcia, Jose Luis</mods:namePart>
  </mods:name>
3. <mods:name>
  1. <mods:namePart>Cazorla Lopez, Diego C.</mods:namePart>
  </mods:name>
4. <mods:name>
  1. <mods:namePart>Valero Lara, Pedro</mods:namePart>
  </mods:name>
5. <mods:name>
  1. <mods:namePart>Arias Antunez, Enrique</mods:namePart>
  </mods:name>
6. <mods:extension>
  1. <mods:dateAvailable encoding="iso8601">2012-01-13T07:10:17Z</mods:dateAvailable>
  </mods:extension>
7. <mods:extension>
  1. <mods:dateAccessioned encoding="iso8601">2012-01-13T07:10:17Z</mods:dateAccessioned>
  </mods:extension>
8. <mods:originInfo>
  1. <mods:dateIssued encoding="iso8601">2011</mods:dateIssued>
  </mods:originInfo>
9. <mods:identifier type="citation">Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</mods:identifier>
10. <mods:identifier type="isbn">978-3-642-21927-6</mods:identifier>
11. <mods:identifier type="issn">0302-9743</mods:identifier>
12. <mods:identifier type="uri">http://hdl.handle.net/10578/1773</mods:identifier>
13. <mods:abstract>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</mods:abstract>
14. <mods:language>
  1. <mods:languageTerm>es</mods:languageTerm>
  </mods:language>
15. <mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
16. <mods:subject>
  1. <mods:topic>Ciencias de la computación y tecnología informática</mods:topic>
  </mods:subject>
17. <mods:titleInfo>
  1. <mods:title>A gpu-based implementation for range queries on spaghettis data structure</mods:title>
  </mods:titleInfo>
18. <mods:genre>info:eu-repo/semantics/article</mods:genre>
</mods:mods>

ore

<?xml version="1.0" encoding="UTF-8" ?>

<atom:entry schemaLocation="http://www.w3.org/2005/Atom http://www.kbcafe.com/rss/atom.xsd.xml">
1. <atom:id>http://hdl.handle.net/10578/1773/ore.xml</atom:id>
2. <atom:link href="http://hdl.handle.net/10578/1773" rel="alternate" />
3. <atom:link href="http://hdl.handle.net/10578/1773/ore.xml" rel="http://www.openarchives.org/ore/terms/describes" />
4. <atom:link href="http://hdl.handle.net/10578/1773/ore.xml#atom" rel="self" type="application/atom+xml" />
5. <atom:published>2012-01-13T07:10:17Z</atom:published>
6. <atom:updated>2012-01-13T07:10:17Z</atom:updated>
7. <atom:source>
  1. <atom:generator>Ruidera UCLM</atom:generator>
  </atom:source>
8. <atom:title>A gpu-based implementation for range queries on spaghettis data structure</atom:title>
9. <atom:author>
  1. <atom:name>Uribe Paredes, Roberto</atom:name>
  </atom:author>
10. <atom:author>
  1. <atom:name>Sanchez Garcia, Jose Luis</atom:name>
  </atom:author>
11. <atom:author>
  1. <atom:name>Cazorla Lopez, Diego C.</atom:name>
  </atom:author>
12. <atom:author>
  1. <atom:name>Valero Lara, Pedro</atom:name>
  </atom:author>
13. <atom:author>
  1. <atom:name>Arias Antunez, Enrique</atom:name>
  </atom:author>
14. <atom:category label="Aggregation" scheme="http://www.openarchives.org/ore/terms/" term="http://www.openarchives.org/ore/terms/Aggregation" />
15. <atom:category scheme="http://www.openarchives.org/ore/atom/modified" term="2012-01-13T07:10:17Z" />
16. <atom:category label="DSpace Item" scheme="http://www.dspace.org/objectModel/" term="DSpaceItem" />
17. <atom:link href="http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf" length="166953" rel="http://www.openarchives.org/ore/terms/aggregates" title="fi_1320857362-ruribeiccsa2011cameraready.pdf" type="application/pdf" />
18. <oreatom:triples>
  1. <rdf:Description about="http://hdl.handle.net/10578/1773/ore.xml#atom">
    1. <rdf:type resource="http://www.dspace.org/objectModel/DSpaceItem" />
    2. <dcterms:modified>2012-01-13T07:10:17Z</dcterms:modified>
    </rdf:Description>
  2. <rdf:Description about="http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf">
    1. <rdf:type resource="http://www.dspace.org/objectModel/DSpaceBitstream" />
    2. <dcterms:description>ORIGINAL</dcterms:description>
    </rdf:Description>
  3. <rdf:Description about="http://localhost:8080/xmlui/bitstream/10578/1773/2/license.txt">
    1. <rdf:type resource="http://www.dspace.org/objectModel/DSpaceBitstream" />
    2. <dcterms:description>LICENSE</dcterms:description>
    </rdf:Description>
  4. <rdf:Description about="http://localhost:8080/xmlui/bitstream/10578/1773/3/fi_1320857362-ruribeiccsa2011cameraready.pdf.txt">
    1. <rdf:type resource="http://www.dspace.org/objectModel/DSpaceBitstream" />
    2. <dcterms:description>TEXT</dcterms:description>
    </rdf:Description>
  </oreatom:triples>
</atom:entry>

qdc

<?xml version="1.0" encoding="UTF-8" ?>

<qdc:qualifieddc schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
1. <dc:title>A gpu-based implementation for range queries on spaghettis data structure</dc:title>
2. <dc:subject>Ciencias de la computación y tecnología informática</dc:subject>
3. <dcterms:abstract>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</dcterms:abstract>
4. <dcterms:dateAccepted>2012-01-13T07:10:17Z</dcterms:dateAccepted>
5. <dcterms:available>2012-01-13T07:10:17Z</dcterms:available>
6. <dcterms:created>2012-01-13T07:10:17Z</dcterms:created>
7. <dcterms:issued>2011</dcterms:issued>
8. <dc:type>info:eu-repo/semantics/article</dc:type>
9. <dc:identifier>Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</dc:identifier>
10. <dc:identifier>978-3-642-21927-6</dc:identifier>
11. <dc:identifier>0302-9743</dc:identifier>
12. <dc:identifier>http://hdl.handle.net/10578/1773</dc:identifier>
13. <dc:language>es</dc:language>
14. <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
15. <dc:publisher>Springer-Verlag</dc:publisher>
</qdc:qualifieddc>

rdf

<?xml version="1.0" encoding="UTF-8" ?>

<rdf:RDF schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
1. <ow:Publication about="oai:Ruidera:10578/1773">
  1. <dc:title>A gpu-based implementation for range queries on spaghettis data structure</dc:title>
  2. <dc:creator>Uribe Paredes, Roberto</dc:creator>
  3. <dc:creator>Sanchez Garcia, Jose Luis</dc:creator>
  4. <dc:creator>Cazorla Lopez, Diego C.</dc:creator>
  5. <dc:creator>Valero Lara, Pedro</dc:creator>
  6. <dc:creator>Arias Antunez, Enrique</dc:creator>
  7. <dc:subject>Ciencias de la computación y tecnología informática</dc:subject>
  8. <dc:description>Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</dc:description>
  9. <dc:date>2012-01-13T07:10:17Z</dc:date>
  10. <dc:date>2012-01-13T07:10:17Z</dc:date>
  11. <dc:date>2011</dc:date>
  12. <dc:type>info:eu-repo/semantics/article</dc:type>
  13. <dc:identifier>Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</dc:identifier>
  14. <dc:identifier>978-3-642-21927-6</dc:identifier>
  15. <dc:identifier>0302-9743</dc:identifier>
  16. <dc:identifier>http://hdl.handle.net/10578/1773</dc:identifier>
  17. <dc:language>es</dc:language>
  18. <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  19. <dc:publisher>Springer-Verlag</dc:publisher>
  </ow:Publication>
</rdf:RDF>

xoai

<?xml version="1.0" encoding="UTF-8" ?>

<metadata schemaLocation="http://www.lyncode.com/xoai http://www.lyncode.com/xsd/xoai.xsd">
1. <element name="dc">
  1. <element name="contributor">
    1. <element name="author">
      1. <element name="es_ES">
        <field name="value">Uribe Paredes, Roberto</field>
        <field name="value">Sanchez Garcia, Jose Luis</field>
        <field name="value">Cazorla Lopez, Diego C.</field>
        <field name="value">Valero Lara, Pedro</field>
        <field name="value">Arias Antunez, Enrique</field>
        </element>
      </element>
    </element>
  2. <element name="date">
    1. <element name="accessioned">
      1. <element name="none">
        <field name="value">2012-01-13T07:10:17Z</field>
        </element>
      </element>
    2. <element name="available">
      1. <element name="none">
        <field name="value">2012-01-13T07:10:17Z</field>
        </element>
      </element>
    3. <element name="issued">
      1. <element name="es_ES">
        <field name="value">2011</field>
        </element>
      </element>
    </element>
  3. <element name="identifier">
    1. <element name="citation">
      1. <element name="es_ES">
        <field name="value">Lecture notes in computer science vol. 6782 (intl. Conf. On computational science and its applications, iccsa), 2011, 6782: 615-629</field>
        </element>
      </element>
    2. <element name="isbn">
      1. <element name="es_ES">
        <field name="value">978-3-642-21927-6</field>
        </element>
      </element>
    3. <element name="issn">
      1. <element name="es_ES">
        <field name="value">0302-9743</field>
        </element>
      </element>
    4. <element name="uri">
      1. <element name="none">
        <field name="value">http://hdl.handle.net/10578/1773</field>
        </element>
      </element>
    </element>
  4. <element name="description">
    1. <element name="abstract">
      1. <element name="es_ES">
        <field name="value">Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10. Keywords: Databases ? similarity search ? metric spaces ? algorithms ? data structures ? parallel processing ? GPU ? CUDA</field>
        </element>
      </element>
    </element>
  5. <element name="format">
    1. <element name="en_US">
      1. <field name="value">text/plain</field>
      </element>
    </element>
  6. <element name="language">
    1. <element name="iso">
      1. <element name="en_US">
        <field name="value">es</field>
        </element>
      </element>
    </element>
  7. <element name="publisher">
    1. <element name="es_ES">
      1. <field name="value">Springer-Verlag</field>
      </element>
    </element>
  8. <element name="rights">
    1. <element name="en_US">
      1. <field name="value">info:eu-repo/semantics/openAccess</field>
      </element>
    </element>
  9. <element name="subject">
    1. <element name="es_ES">
      1. <field name="value">Ciencias de la computación y tecnología informática</field>
      </element>
    </element>
  10. <element name="title">
    1. <element name="es_ES">
      1. <field name="value">A gpu-based implementation for range queries on spaghettis data structure</field>
      </element>
    </element>
  11. <element name="type">
    1. <element name="en_US">
      1. <field name="value">info:eu-repo/semantics/article</field>
      </element>
    </element>
  </element>
2. <element name="bundles">
  1. <element name="bundle">
    1. <field name="name">ORIGINAL</field>
    2. <element name="bitstreams">
      1. <element name="bitstream">
        <field name="name">fi_1320857362-ruribeiccsa2011cameraready.pdf</field>
        <field name="format">application/pdf</field>
        <field name="size">166953</field>
        <field name="url">http://localhost:8080/xmlui/bitstream/10578/1773/1/fi_1320857362-ruribeiccsa2011cameraready.pdf</field>
        <field name="checksum">5b6f1f461060343241dd20cd343b88ed</field>
        <field name="checksumAlgorithm">MD5</field>
        <field name="sid">1</field>
        </element>
      </element>
    </element>
  2. <element name="bundle">
    1. <field name="name">LICENSE</field>
    2. <element name="bitstreams">
      1. <element name="bitstream">
        <field name="name">license.txt</field>
        <field name="format">text/plain</field>
        <field name="size">2590</field>
        <field name="url">http://localhost:8080/xmlui/bitstream/10578/1773/2/license.txt</field>
        <field name="checksum">8e261cdacc955cb817dbbd174c18375a</field>
        <field name="checksumAlgorithm">MD5</field>
        <field name="sid">2</field>
        </element>
      </element>
    </element>
  3. <element name="bundle">
    1. <field name="name">TEXT</field>
    2. <element name="bitstreams">
      1. <element name="bitstream">
        <field name="name">fi_1320857362-ruribeiccsa2011cameraready.pdf.txt</field>
        <field name="originalName">fi_1320857362-ruribeiccsa2011cameraready.pdf.txt</field>
        <field name="description">Extracted text</field>
        <field name="format">text/plain</field>
        <field name="size">35290</field>
        <field name="url">http://localhost:8080/xmlui/bitstream/10578/1773/3/fi_1320857362-ruribeiccsa2011cameraready.pdf.txt</field>
        <field name="checksum">16ebaf2dcc971a3eea8afb9ead91e507</field>
        <field name="checksumAlgorithm">MD5</field>
        <field name="sid">3</field>
        </element>
      </element>
    </element>
  </element>
3. <element name="others">
  1. <field name="handle">10578/1773</field>
  2. <field name="identifier">oai:Ruidera:10578/1773</field>
  3. <field name="lastModifyDate">2015-09-22 03:10:13.447</field>
  </element>
4. <element name="repository">
  1. <field name="name">Ruidera UCLM</field>
  2. <field name="mail">ruidera@uclm.es</field>
  </element>
5. <element name="license">
  1. <field name="bin">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</field>
  </element>
</metadata>