Using ICENI to run parameter sweep applications across multiple Grid resources

Using ICENI to run parameter sweep applications across

multiple Grid resourcesMurtaza Gulamali

Stephen McGough, Steven Newhouse, John Darlington

London e-Science Centre

Department of Computing, Imperial College London

Case Studies on Grid Applications – GGF10

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Contents

1. The GENIE project

2. The ICENI middleware

3. GENIE as an ICENI application

4. Summary and conclusions

5. Acknowledgements

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The GENIE projectBackground

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

AtmosphericCO2

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.

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The GENIE projectBackground

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.

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The GENIE projectPrevious 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!

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The GENIE projectPrevious 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

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The ICENI middlewareBackground

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

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The ICENI middlewareApplication development in ICENI

ICENI uses a component programming model to describe Grid applications.

application development application composition Example: linear equation solver

matrixsource

vectorsource

linear equation

solver

vectorsink

linear equation

solver

Cholsky decomposition

LU decomposition

linear equation

solver

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The ICENI middlewareApplication development in ICENI

service list composition pane parameters

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GENIE as an ICENI applicationParameter sweep as component app.

setup component

GENIEbinary

component

archive component

GENIEbinary

component

GENIEbinary

component

splitter component

collator component

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GENIE as an ICENI applicationExecuting over multiple resources

Beowulf cluster

setup component

GENIEbinary

component

archive component

GENIEbinary

component

resource launcher

resource launcher

Condor pool

splitter component

collator component

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GENIE as an ICENI applicationResults

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.

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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)

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Acknowledgements

My co-authors:

– Dr. Stephen McGough, Dr. Steven Newhouse, Prof. John Darlington.

The ICENI development team:

– http://www.lesc.ac.uk/iceni/ The GENIE team:

– http://www.genie.ac.uk/