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Learning to Classify Parallel Input/Output Access Patterns.

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Τίτλος: Learning to Classify Parallel Input/Output Access Patterns.
Συγγραφείς: Madhyastha, Tara M., Reed, Daniel A.
Πηγή: IEEE Transactions on Parallel & Distributed Systems. Aug2002, Vol. 13 Issue 8, p802. 12p. 2 Black and White Photographs, 2 Diagrams, 5 Charts, 5 Graphs.
Θεματικοί όροι: *Algorithms, *Artificial neural networks, File processing (Computer science)
Περίληψη: Examines the input/output access pattern in parallel file systems. Use of learning algorithms to classify input/output access patterns; Utilization of artificial neural network in recognizing access patterns; Accommodation of various high-level interfaces in the access pattern classification model.
Βάση Δεδομένων: Business Source Index
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An: 7284242
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PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1171.3779296875
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  Data: Learning to Classify Parallel Input/Output Access Patterns.
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  Data: Examines the input/output access pattern in parallel file systems. Use of learning algorithms to classify input/output access patterns; Utilization of artificial neural network in recognizing access patterns; Accommodation of various high-level interfaces in the access pattern classification model.
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/TPDS.2002.1028437
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 802
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      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: File processing (Computer science)
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      – TitleFull: Learning to Classify Parallel Input/Output Access Patterns.
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            NameFull: Madhyastha, Tara M.
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              Text: Aug2002
              Type: published
              Y: 2002
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              Value: 13
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              Value: 8
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