Mathieu Leclaire // Romain Reuillon // Mark Hammons // Jonathan Passerat-Palmbach
ISCPIF // BioEmergences // FBI // Imperial College London
When you want to run a large scale study of the brain...
But the deadline for MICCAI is getting so close...
You feel like you'll never get those results in a reasonable time
Hopefully your applications are naturally parallel algorithms \o/
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European Grid Infrastructure |
It exposes a workflow formalism for describing an experiment | ![]() |
It transparently delegates computational loads to massively parallel environments | ![]() |
Prototype small
Experiment large
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A Task runs an executable, |
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receives and produces Variables. |
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Variables navigate from one Task to another by means of Transitions |
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eventually doing Loops. |
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Design you experiment in OpenMOLE | At runtime |
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The same Task can be run localy |
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or by taking leverage of the local multicores |
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or on a Cluster (PBS for instance) |
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or on the Grid. |
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val i1 = Prototype[Int]("i1") val i2 = Prototype[Int]("i2") val j = Prototype[Int]("j") val hello = GroovyTask("hello", "j = Model.compute(i1, i2)") hello addInput i1 hello addInput i2 hello addOutput j hello addLib "/path/to/model.jar" val exploration = ExplorationTask( "exploration", Factor(i1, 0 to 100 by 2 toDomain) x Factor(i2, new UniformIntDistribution take 10) ) val ex = exploration -< (hello by 10 on biomed) toExecution ex.start
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@OpenMOLE |