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000864600 1001_ $$0P:(DE-Juel1)168169$$aKlijn, Wouter$$b0$$eCorresponding author$$ufzj
000864600 1112_ $$aThe 2019 International Conference on High Performance Computing & Simulation$$cDublin$$d2019-07-15 - 2019-07-19$$gHPCS 2019$$wIreland
000864600 245__ $$aStaged deployment of interactive multi-application HPC workflows
000864600 260__ $$bIEEE$$c2020
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000864600 520__ $$aRunning scientific workflows on a supercomputer can be a daunting task for a scientific domain specialist. Workflow management solutions (WMS) are a standard method for reducing the complexity of application deployment on high performance computing (HPC) infrastructure. We introduce the design for a middleware system that extends and combines the functionality from existing solutions in order to create a high-level, staged user-centric operation/deployment model. This design addresses the requirements of several use cases in the life sciences, with a focus on neuroscience. In this manuscript we focus on two use cases: 1) three coupled neuronal simulators (for three different space/time scales) with in-transit visualization and 2) a closed-loop workflow optimized by machine learning, coupling a robot with a neural network simulation. We provide a detailed overview of the application-integrated monitoring in relationship with the HPC job. We present here a novel usage model for large scale interactive multi-application workflows running on HPC systems which aims at reducing the complexity of deployment and execution, thus enabling new science.
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000864600 7001_ $$0P:(DE-Juel1)165859$$aDiaz, Sandra$$b1$$ufzj
000864600 7001_ $$0P:(DE-Juel1)151166$$aMorrison, Abigail$$b2$$ufzj
000864600 7001_ $$0P:(DE-Juel1)161525$$aPeyser, Alexander$$b3$$ufzj
000864600 773__ $$a10.1109/HPCS48598.2019.9188104
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