Grid Enabled Pattern Matching within the DAME e-Science Pilot Project Jim Austin Computer Science University of York

All hands 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.

All hands Introduction Objectives of DAME Diagnostics issues How AURA fits in AURA-G – GRID enabled AURA Where are we now?

All hands 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

All hands Engine flight data Airline office Maintenance Centre European data center London Airport New York Airport American data center Grid Diagnostics centre

All hands Diagnostic issues The system must analyse and report –Novel engine operation –Identify any cause of events –Do this quickly Data –Large (many Tb)

All hands Data – Zmod plots

All hands Proposed pattern matching process Quote Novelty indication Data used to identify novelty Data reduction processes Features Data stores/ data warehouse Diagnostic station Engine data Data to be searched for Match requests AURA-G Diagnosis

All hands 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.

All hands AURA parallel implementation 28 dedicated PCI based processors Beowulf configuration 3.5Gb memory size Cortex-1

All hands Basic CMM inputs  Samples of tracked orders

All hands Data sample DM coding CMM Matching previous events Simple example of processing chain

All hands Typical pre-processing DM coding (1 up 0 down) Fast Preserves information Produces a binary vector Time Frequency

All hands Quote Novelty indication Data used to identify novelty Data reduction processes Features Data stores/ data warehouse Diagnostic station Engine data Data to be searched for Pattern match results Match requests AURA-G GRID Diagnosis

All hands AURA-G This is a Globus enabled AURA implementation. Developed under DAME Will be available end of 2002 for use in other problems.

All hands AURA-G Support of scalable pattern matching Supports distributed search, across multiple CMM engines at different sites OGSA compliant

All hands Conclusions AURA-G enabling fast access to large, complex data. Available for other applications Diagnostic framework in DAME applicable elsewhere. DAME web site: AURA website: – –