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

2. All hands 20022 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.

3. All hands 20023 Introduction Objectives of DAME Diagnostics issues How AURA fits in AURA-G – GRID enabled AURA Where are we now?

4. All hands 20024 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

5. All hands 20025 Engine flight data Airline office Maintenance Centre European data center London Airport New York Airport American data center Grid Diagnostics centre

6. All hands 20026 Diagnostic issues The system must analyse and report –Novel engine operation –Identify any cause of events –Do this quickly Data –Large (many Tb)

7. All hands 20027 Data – Zmod plots

8. All hands 20028 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

9. All hands 20029 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.

10. All hands 200210 AURA parallel implementation 28 dedicated PCI based processors Beowulf configuration 3.5Gb memory size Cortex-1

11. All hands 200211 Basic CMM inputs  Samples of tracked orders

12. All hands 200212 Data sample DM coding CMM Matching previous events Simple example of processing chain

13. All hands 200213 Typical pre-processing DM coding 01101111011110111 (1 up 0 down) Fast Preserves information Produces a binary vector Time Frequency

14. All hands 200214 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

15. All hands 200215 AURA-G This is a Globus enabled AURA implementation. Developed under DAME Will be available end of 2002 for use in other problems.

16. All hands 200216 AURA-G Support of scalable pattern matching Supports distributed search, across multiple CMM engines at different sites OGSA compliant

17. All hands 200217 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/damewww.cs.york.ac.uk/dame AURA website: –www.cs.york.ac.uk/arch/nn/aura.html –www.cybula.com