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Mobile Analyzer

Marko Niinimaki Helsinki Institute of Physics at CERN. Mobile Analyzer. Basic Ideas. ''GridWire'' type peer-to-peer computing prototype. Sends java JAR files (where one class conforms to a certain interface) to ''registered'' computing nodes (that contain the data).

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Mobile Analyzer

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  1. Marko Niinimaki Helsinki Institute of Physics at CERN Mobile Analyzer

  2. Basic Ideas • ''GridWire'' type peer-to-peer computing prototype. • Sends java JAR files (where one class conforms to a certain interface) to ''registered'' computing nodes (that contain the data). • Results and job meta sent back to the client. • Uses proxy authorization, secure file transfers etc.

  3. ..moreover.. • Extremely easy to install and run, requires only a JDK platform. • ''Login, start job, logout, come back later'' principle. • Previously used LDAP for job meta data reporting (and checkpointing). Recent versions can use other repositories, too. • Any Mobile Analyzer node can be both a client and a server in the network.

  4. Extensions • Retrive data from Spitfire • ''Result collector'': spawn the same job (maybe with different parameters) to several nodes. Wait for the computations to finish in each one and aggregate the results. • ''Visualizer'': an plug-in class can display ZEBRA histograms (results of CMS simulations).

  5. Starting the application, creating a job

  6. Job Monitoring

  7. Results

  8. Credits • Developed by Mika Kaki, Juho Karppinen of HIP@CERN. • Physics visualisation by Mika Kaki, John White based on JAS (Java analysis studio) classes. • Combined with Spitfire by Tapio Niemi (University of Tampere) to locally analyse GB's of data from different Spitfire installations and send the results to an OLAP server (by IBM).

  9. Publications and further info • wikihip.cern.ch • White, Niemi, Karppinen, Niinimaki: Mobile Analyzer, a novel concept for next generation distributed computing (CCGrids 2003, Japan, poster). • Niemi, Niinimaki, Nummenmaa, Thanisch: Constructing an OLAP cube from distributed XML data, ACM 5th Workshop on Data Warehousing and OLAP, McLean, WA, 2002.

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