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    Area of Science:

    • Scientific Visualization
    • Computer Graphics
    • Computational Science

    Background:

    • Structured Adaptive Mesh Refinement (Structured AMR) is crucial for efficient scientific simulations, adapting domain resolution to reduce computation and storage.
    • Rendering complex Structured AMR data efficiently remains a significant challenge in scientific visualization.

    Purpose of the Study:

    • To develop an efficient GPU-based ray tracing approach for rendering Structured AMR data.
    • To enable interactive volume and iso-surface rendering of complex AMR datasets on individual workstations.

    Main Methods:

    • Utilized a combination of two data structures to optimize ray integration frequency and data access for ray tracing.
    • Leveraged RTX ray tracing hardware for surface rendering, ray marching, space skipping, and adaptive sampling.
    • Implemented interactive transfer function and iso-surfacing threshold adjustments.

    Main Results:

    • Achieved high performance rendering of Structured AMR data with minimal memory overhead.
    • Enabled interactive, high-quality visualization of complex AMR datasets on GPU workstations.
    • Demonstrated efficient ray tracing for both volume and iso-surface rendering.

    Conclusions:

    • The proposed method offers an efficient solution for rendering Structured AMR data, overcoming previous rendering challenges.
    • The approach facilitates interactive exploration of complex simulation results, enhancing scientific discovery.
    • This technique significantly improves the accessibility and quality of visualizing adaptive mesh refinement data.