Using ICENI to run parameter sweep applications across multiple Grid resources Murtaza Gulamali Stephen McGough, Steven Newhouse, John Darlington London e-Science Centre Department of Computing, Imperial College London Case Studies on Grid Applications – GGF10

2 Contents 1.The GENIE project 2.The ICENI middleware 3.GENIE as an ICENI application 4.Summary and conclusions 5.Acknowledgements

3 The GENIE project Background  Grid ENabled Integrated Earth system model.  Investigate long term changes to the Earth’s climate (i.e. global warming) by integrating numerical models of various components of the Earth system. 3D atmosphere 3D ocean 2D sea ice Atmospheric CO 2 2D land surface Land biogeochemistry Ocean biogeochemisty Ocean sediments 3D ice sheets Schematic diagram of model framework for GENIE. Courtesy of T. Lenton, CEH Edinburgh, UK.

4 The GENIE project Background  Grid ENabled Integrated Earth system model.  Investigate long term changes to the Earth’s climate (i.e. global warming) by integrating numerical models of various components of the Earth system.  Require a Grid infrastructure to: –flexibly couple together components to form a unified Earth System Model (ESM). –execute the resultant ESM efficiently and accurately. –archive and share the resultant data produced by the model. –provide a high-level open access system to allow a virtual organisation of Earth System modellers to collaborate.

5 The GENIE project Previous scientific work  Investigate the vulnerability of the thermohaline circulation of the world ocean using a prototype model consisting of just 3 coupled components.  Run simulation across two different parameter ranges.  perform 31  31 = 961 individual simulations.  parameter sweep application!

6 The GENIE project Previous e-scientific work  Provided Grid infrastructure to support this activity… –flocked Condor pool between three institutions. –web-portal to allow experiment management. –database management system (based on Geodise) to allow data archiving and retrieval.  Disadvantages of this infrastructure… –firewalls!… between institutions hosting Condor pools. –web-portal not very flexible… model and parameter choices hard-coded. –true resource brokering not taking place… all compute and database resources belonging to virtual organisation not utilised.  Solution: use ICENI middleware

7 The ICENI middleware Background  IC e-Science Networked Infrastructure.  Developed by LeSC Grid Middleware Group.  Service oriented Grid middleware.  Represents compute, storage and software resources as services.  Services can communicate using standard protocols (eg. Jini, SOAP, JXTA).  ICENI provides an end-to-end middleware consisting of: –Grid service infrastructure –dynamic service management framework –application toolkit

8 The ICENI middleware Application development in ICENI  ICENI uses a component programming model to describe Grid applications.  application development  application composition  Example: linear equation solver matrix source vector source linear equation solver vector sink linear equation solver Cholsky decomposition LU decomposition linear equation solver

9 The ICENI middleware Application development in ICENI service listcomposition paneparameters

10 GENIE as an ICENI application Parameter sweep as component app. setup component GENIE binary component archive component GENIE binary component GENIE binary component splitter component collator component

11 GENIE as an ICENI application Executing over multiple resources Beowulf cluster setup component GENIE binary component archive component GENIE binary component resource launcher Condor pool splitter component collator component

12 GENIE as an ICENI application Results  Using ICENI, ran 4 GENIE parameter sweep experiments on Beowulf Cluster (using Sun Grid Engine) and Linux PC based Condor pool. –Sun Grid Engine: 481 jobs –Condor pool: 480 jobs –Total: (31  31 =)961 jobs  Find that ICENI takes ~2 minutes to schedule and submit jobs to both high throughput job managers.  Each experiment took ~5 days to run.

13 Summary and conclusions  Are able to execute GENIE parameter sweep experiments across multiple resources administered by members of virtual organisation.  Execution time same as before but: –Can leverage all the flexibility of a service oriented Grid middleware. –Can create ICENI Grid based on resources owned and federated by collaborators in the virtual organisation. –Don’t have to contend with firewalls… (sort of)

14 Acknowledgements  My co-authors: –Dr. Stephen McGough, Dr. Steven Newhouse, Prof. John Darlington.  The ICENI development team: –  The GENIE team: –