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The CARMEN Science Cloud

The CARMEN Science Cloud. Paul Watson Computing Science Newcastle University, UK Paul.Watson@ncl.ac.uk. Research Challenge. Understanding the brain is the greatest informatics challenge Enormous implications for science: Medicine Biology Computer Science

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The CARMEN Science Cloud

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  1. The CARMEN Science Cloud Paul Watson Computing Science Newcastle University, UK Paul.Watson@ncl.ac.uk

  2. Research Challenge Understanding the brain is the greatest informatics challenge • Enormous implications for science: • Medicine • Biology • Computer Science 100,000 scientists are working on this

  3. Neuroinformatics Problems • Data is: • expensive to collect but rarely shared • in proprietary formats & locally described • The result is: • a shortage of analysis techniques that can be applied across neuronal systems • limited interaction between research centres with complementary expertise

  4. UK EPRSC e-Science Pilot $8M (2006-10) 20 Investigators CARMEN Project Stirling St. Andrews Newcastle York Manchester Sheffield Leicester Cambridge Warwick Imperial Plymouth

  5. Focus on Neural Activity • raw voltage signal data from single or multi-electrode arrays neurone 1 neurone 2 neurone 3 cracking the neural code

  6. Epilepsy Exemplar • Data analysis guides surgeon during operation • Data stored for further analysis WARNING! The next 2 Slides show an exposed human brain

  7. CARMEN e-Science Requirements • Store • very large data storage (100TB+) • Analyse • suite of neuroinformatics services • support data intensive analysis • Automate • workflow • Share • under user-control

  8. CARMEN Cloud Architecture User access over Internet (typically via browser) Users upload data & services Users run analyses Data storage and analysis

  9. Cloud Design Options Science App 1 Science App n .... Science Cloud Platform Science App 1 Science App n .... Cloud Infrastructure: Storage & Compute Cloud Infrastructure: Storage & Compute

  10. CARMEN Cloud Filestore with Pattern Search Workflow Security Database Workflow Enactment Metadata Processing Browsers & Rich Clients Service Repository

  11. CARMEN Cloud – technology re-use SRB & Aura SDE Filestore with Pattern Search Workflow SQL Server Taverna Security Gold Symba Database Workflow Enactment Dynasoar Metadata Processing Browsers & Rich Clients Service Repository

  12. Example: Running a Workflow

  13. Current State of CARMEN • Working prototype with early users • Now generalising approach with e-Science Central • new code base • + supports range of sciences • + social networking for sharing & collaboration • funded by regional development authority (One NE) • Sustainability is an issue...

  14. Sustainability – Commercial Clouds to the Rescue? • cost of managing & maintaining h/w & s/w • academics are funded to do research, not run a service • Could we use Commercial Clouds? • “Pay-as-you-go” for storage & processing • about to investigate use of Microsoft Cloud • Arjuna Agility “on ramp” to commercial clouds • Still a gap...

  15. A Sustainable Science Cloud Science App 1 Science App n ? .... Science Cloud Platform Problem: delivering the e-science services ? e-Science Central www.inkspotscience.com Commercial Clouds  Storage & Compute

  16. Summary & Further Information • CARMEN is delivering a scalable cloud for neuroscience • www.carmen.org.uk • www.youtube.com/watch?v=2m4EvnlgL8Q • e-Science Central: a science cloud for academic and industrial scientists across NE England • We are building a pay-as-you go Science Cloud for Capability, Agility & Sustainability

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