mlsanityData to 7 Oct 2026

Distributed Neural Representation for Reactive in situ Visualization

arXiv 2304.10516 ↗First posted 28 Mar 2023cs.DC cs.AIcited by 8

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Abstract (arXiv)

Implicit neural representations (INRs) have emerged as a powerful tool for compressing large-scale volume data. This opens up new possibilities for in situ visualization. However, the efficient application of INRs to distributed data remains an underexplored area. In this work, we develop a distributed volumetric neural representation and optimize it for in situ visualization. Our technique eliminates data exchanges between processes, achieving state-of-the-art compression speed, quality and ratios. Our technique also enables the implementation of an efficient strategy for caching large-scale simulation data in high temporal frequencies, further facilitating the use of reactive in situ visualization in a wider range of scientific problems. We integrate this system with the Ascent infrastructure and evaluate its performance and usability using real-world simulations.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 28 of its 98 references that are in the map. First posted on arXiv 28 Mar 2023.

Builds on

28 of 98 references.

References · 28

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16 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 7.

8 papers.

  1. 2026Neural Harmonic Textures for High-Quality Primitive Based Neural Reconstructioncited by 2
  2. 2026ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualizationcited by 2
  3. 2025On the accuracy of implicit neural representations for cardiovascular anatomies and hemodynamic fieldscited by 1
  4. 2026Fixed-Budget Gaussian Volume Encoding with Structure-Aware Allocationcited by 1
  5. 2026NeuVolEx: Implicit Neural Features for Volume Explorationcited by 0
  6. 2026From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Datacited by 0
  7. 2026Direct Topology Tracking in Continuous Implicit Modelscited by 0
  8. 2026DiffusionShadow: Diffusion-based Shadow Caching for Neural Volume Renderingcited by 0