grid enabled pattern matching within the dame e-science pilot project
DESCRIPTION
Grid Enabled Pattern Matching within the DAME e-Science Pilot Project . Jim Austin Computer Science University of York. Rolls-Royce. University of Sheffield, P Fleming. University of Leeds, Peter Dew, Alison McKay. York, J Austin, J McDermid, A Wellings. - PowerPoint PPT PresentationTRANSCRIPT
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Grid Enabled Pattern Matching within the DAME
e-Science Pilot Project
Jim Austin
Computer Science
University of York
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All hands 2002 2
Rolls-Royce
University of Oxford, Lionel Tarassenko.
University of Leeds, Peter Dew, Alison McKay.
York, J Austin, J McDermid, A Wellings.
University of Sheffield, P Fleming.
Rolls-Royce, Derby.
Data Systems and Solutions.
Cybula Ltd.
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Introduction• Objectives of DAME
• Diagnostics issues
• How AURA fits in
• AURA-G – GRID enabled AURA
• Where are we now?
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DAME Objectives• DAME: Distributed Aircraft Maintenance
Environment.
• Demonstrate diagnostic capability on the GRID
• Examine timeliness properties of the GRID
• Demonstrate on the RR Aeroengine diagnostic problem
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Engine flight data
Airline office
Maintenance Centre
European data center
London Airport
New York Airport
American data center
GridDiagnostics centre
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Diagnostic issues• The system must analyse and report
– Novel engine operation– Identify any cause of events– Do this quickly
• Data– Large (many Tb)
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Data – Zmod plots
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Proposed pattern matchingprocess
QuoteNovelty indication
Data used to identify novelty
Data reductionprocesses
Features
Data stores/data warehouse
Diagnostic stationEngine data
Data to be searched for
Match requests
AURA-G
Diagnosis
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How does AURA contribute• Search technology for multi-media data
• Parallel pattern match engine based on neural networks.
• Built on Correlation Matrix Memories.
• High performance Beowulf and dedicated hardware implementations.
• Commercially sold by Cybula Ltd.
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AURA parallel implementation 28 dedicated PCI based processors
Beowulf configuration3.5Gb memory size
Cortex-1
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Basic CMM
inputs
Samples of tracked orders
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Data sample DM coding CMM
Matching previous events
Simple example of processing chain
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Typical pre-processing
DM coding01101111011110111
(1 up 0 down)
FastPreserves informationProduces a binary vector
Time
Fre
quen
cy
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QuoteNovelty indication
Data used to identify novelty
Data reductionprocesses
Features
Data stores/data warehouse
Diagnostic stationEngine data
Data to be searched for Pattern match
results
Match requests
AURA-G
GRID
Diagnosis
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AURA-G
• This is a Globus enabled AURA implementation.
• Developed under DAME
• Will be available end of 2002 for use in other problems.
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AURA-G
• Support of scalable pattern matching
• Supports distributed search, across multiple CMM engines at different sites
• OGSA compliant
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Conclusions• AURA-G enabling fast access to large, complex
data.• Available for other applications• Diagnostic framework in DAME applicable
elsewhere.• DAME web site: www.cs.york.ac.uk/dame• AURA website:
– www.cs.york.ac.uk/arch/nn/aura.html– www.cybula.com