Improvement in interactive remote in situ visualization using SIMD-aware function parser and asynchronous data I/O

Kawamura, Takuma; Idomura, Yasuhiro

doi:10.1007/s12650-020-00652-z

J Vis

2020

DOI: 10.1007/s12650-020-00652-z

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Improvement in interactive remote in situ visualization using SIMD-aware function parser and asynchronous data I/O

Takuma Kawamura

Yasuhiro Idomura

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Cited by 2 publications

References 13 publications

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Interactive steering on in situ particle-based volume rendering framework

Kawamura,

Hasegawa,

Idomura

2023

J Vis

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The development of supercomputers and multi-scale computational fluid dynamics (CFD) models based on adaptive mesh refinement (AMR) enabled fast, large-scale, and high fidelity CFD simulations. Interactive in situ steering is an effective tool for debugging, searching for optimal solutions, and analyzing inverse problems in such 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 and asynchronous communication of steering parameters, compressed visualization 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, which computes the lattice Boltzmann method on the block AMR grid using GPU supercomputers. In the numerical experiment, we address an inverse problem to find a pollutant source from the observation data at monitoring points and demonstrate the effectiveness of the human-in-the-loop approach via the in situ steering framework. Graphical abstract

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Interactive steering on in situ particle-based volume rendering framework

Kawamura,

Hasegawa,

Idomura

2023

J Vis

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Extension of particle-based in-situ visualization for multipoint VR visualization

Kawamura,

Shimomura,

Osaki

et al. 2024

EPJ Web Conf.

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In the field of nuclear engineering, complex simulations on exascale supercomputers generate large-scale data. To facilitate efficient analysis of such simulation data, one needs to share them among scientists at remote locations. However, data I/O and data transfer for such large-scale data are quite costly. To resolve these issues, we developed a remote in-situ visualization system IS-PBVR based on the particle-based volume rendering (PBVR), which is suitable for parallel processing on modern supercomputers. In this study, we extend IS-PBVR for VR visualization on multiple client PCs, thus developing a multi-point remote VR visualization. We apply this technique to fluid simulations on GPU-based supercomputers and verify its utility by sharing in-situ VR visualization between multiple client PCs.

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Improvement in interactive remote in situ visualization using SIMD-aware function parser and asynchronous data I/O

Cited by 2 publications

References 13 publications

Interactive steering on in situ particle-based volume rendering framework

Interactive steering on in situ particle-based volume rendering framework

Extension of particle-based in-situ visualization for multipoint VR visualization

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