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Co-Scheduling Ensembles of In Situ Workflows
DescriptionMolecular dynamics (MD) simulations are widely used to study large-scale molecular systems. However, reaching the necessary timescale to detect rare processes is challenging, even with modern supercomputers. To overcome the timescale limitation, the simulation of a long MD trajectory is replaced by multiple short-range simulations executed simultaneously in an ensemble. Analyses are usually co-scheduled with these simulations to efficiently process large volumes of data in situ. Executing a workflow ensemble of simulations and their in situ analyses requires sophisticated management of computational resources so that they are not slowing down each other. In this paper, we propose an efficient method to co-schedule and allocate resources for a workflow ensemble such that the makespan is minimized. We evaluate the proposed approach using an accurate simulator based on the WRENCH simulation framework. Results demonstrate the significance of co-scheduling simulations and in situ analyses that couple data together to benefit from data locality.
Cloud and Distributed Computing
In Situ Processing
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