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Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro
Journal of Visualization, 27(1), p.89 - 107, 2024/02
Times Cited Count：0 Percentile：0.01(Computer Science, Interdisciplinary Applications)Interactive in-situ steering is an effective tool for debugging, searching for optimal solutions, and analyzing inverse problems in fast and large-scale computational fluid dynamics (CFD) simulations. We propose an interactive in-situ steering framework for large-scale CFD simulations on GPU supercomputers. This framework employs in-situ particle-based volume rendering (PBVR), in-situ data sampling, and a file-based control that enables interactive communication of steering parameters, compressed particle data, and sampled monitoring data between supercomputers and user PCs. The parallelized PBVR is processed on the host CPU to avoid interference with CFD simulations on the GPU. We apply the proposed framework to a real-time plume dispersion analysis code CityLBM on GPU supercomputers. In the numerical experiment, we address an inverse problem to find a pollutant source from the monitoring data, and demonstrate the effectiveness of the human-in-the-loop approach.
Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro
Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.187 - 192, 2020/10
In order to realize the atmospheric dispersion prediction of pollutants, a fluid simulation by adaptive mesh refinement (AMR) optimized for GPU supercomputer has been developed, and interactive visualization and parameter steering of the simulation results are needed. In this study, we extend particle-based in-situ visualization method for structured grids into AMR, and enables in-situ steering of the simulation parameters by utilizing an in-situ control mechanism via files. By combining the developed method with plume dispersion simulation in urban areas running on a GPU platform, it was shown that human-in-the-loop pollution source search is possible without enormous parameter scanning.
Kawamura, Takuma; Hasegawa, Yuta
no journal, ,
In a large-scale simulation that uses a huge amount of computational resources and runs for a long time on a supercomputer, it is difficult to repeatedly perform recalculation due to adjustment of computational parameters. We have developed a technique for interactive manipulation of simulation parameters by file-based control on an in-situ visualization framework using particle-based volume rendering. We have confirmed that it can be applied to fluid simulation on GPU clusters for interactive visualization and parameter manipulation.
