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2023, Proceedings of the 2023 Winter Simulation Conference, Pages -

Autonomic Orchestration Of In-Situ and In-Transit Data Analytics For Simulation Studies (04b Atto di convegno in volume)

Du Xiaorui, Pimpini Adriano, Piccione Andrea, Meng Zhioxiao, Siguenza-Torres Anibal, Bortoli Stefano, Knoll Alois, Pellegrini Alessandro

Modern parallel/distributed simulations can produce large amounts of data. The historical approach of performing analyses at the end of the simulation is unlikely to cope with modern, extremely large-scale analytics jobs. Indeed, the I/O subsystem can quickly become the global bottleneck. Similarly, processing onthe-fly the data produced by simulations can significantly impair the performance in terms of computational capacity and network load. We present a methodology and reference architecture for constructing an autonomic control system to determine at runtime the best placement for data processing (on simulation nodes or a set of external nodes). This allows for a good tradeoff between the load on the simulation’s critical path and the data communication system. Our preliminary experimentation shows that autonomic orchestration is crucial to improve the global performance of a data analysis system, especially when the simulation node’s rate of data production varies during simulation.
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