Browsing by Author "Zellmann, Stefan"

Now showing 1 - 9 of 9
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    Data Parallel Multi-GPU Path Tracing using Ray Queue Cycling
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Wald, Ingo; Jaros, Milan; Zellmann, Stefan; Bikker, Jacco; Gribble, Christiaan
    We propose a novel approach to data-parallel path tracing on single-node/multi-GPU hardware that builds on ray forwarding, but which aims-above all else-at generality and practicability. We do this by avoiding any attempts at reducing the number of traces or forward operations performed, and instead focus on always using all GPUs' aggregate compute and bandwidth to effectively trace each ray on every GPU. We show that-counter-intuitively-this is both feasible and desirable; and that when run on typical data-center/cloud hardware, the resulting framework not only achieves good performance and scalability, but also comes with significantly fewer limitations, assumptions, or preprocessing requirements than existing techniques.
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    Design and Evaluation of a GPU Streaming Framework for Visualizing Time-Varying AMR Data
    (The Eurographics Association, 2022) Zellmann, Stefan; Wald, Ingo; Sahistan, Alper; Hellmann, Matthias; Usher, Will; Bujack, Roxana; Tierny, Julien; Sadlo, Filip
    We describe a systematic approach for rendering time-varying simulation data produced by exa-scale simulations, using GPU workstations. The data sets we focus on use adaptive mesh refinement (AMR) to overcome memory bandwidth limitations by representing interesting regions in space with high detail. Particularly, our focus is on data sets where the AMR hierarchy is fixed and does not change over time. Our study is motivated by the NASA Exajet, a large computational fluid dynamics simulation of a civilian cargo aircraft that consists of 423 simulation time steps, each storing 2.5 GB of data per scalar field, amounting to a total of 4 TB. We present strategies for rendering this time series data set with smooth animation and at interactive rates using current generation GPUs. We start with an unoptimized baseline and step by step extend that to support fast streaming updates. Our approach demonstrates how to push current visualization workstations and modern visualization APIs to their limits to achieve interactive visualization of exa-scale time series data sets.
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    Faster RTX-Accelerated Empty Space Skipping using Triangulated Active Region Boundary Geometry
    (The Eurographics Association, 2021) Wald, Ingo; Zellmann, Stefan; Morrical, Nate; Larsen, Matthew and Sadlo, Filip
    We describe a technique for GPU and RTX accelerated space skipping of structured volumes that improves on prior work by replacing clustered proxy boxes with a GPU-extracted triangle mesh that bounds the active regions. Unlike prior methods, our technique avoids costly clustering operations, significantly reduces data structure construction cost, and incurs less overhead when traversing active regions.
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    Finding Efficient Spatial Distributions for Massively Instanced 3-d Models
    (The Eurographics Association, 2020) Zellmann, Stefan; Morrical, Nate; Wald, Ingo; Pascucci, Valerio; Frey, Steffen and Huang, Jian and Sadlo, Filip
    Instancing is commonly used to reduce the memory footprint of massive 3-d models. Nevertheless, large production assets often do not fit into the memory allocated to a single rendering node or into the video memory of a single GPU. For memory intensive scenes like these, distributed rendering can be helpful. However, finding efficient data distributions for these instanced 3-d models is challenging, since a memory-efficient data distribution often results in an inefficient spatial distribution, and vice versa. Therefore, we propose a k-d tree construction algorithm that balances these two opposing goals and evaluate our scene distribution approach using publicly available instanced 3-d models like Disney's Moana Island Scene.
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    High-Quality Rendering of Glyphs Using Hardware-Accelerated Ray Tracing
    (The Eurographics Association, 2020) Zellmann, Stefan; Aumüller, Martin; Marshak, Nathan; Wald, Ingo; Frey, Steffen and Huang, Jian and Sadlo, Filip
    Glyph rendering is an important scientific visualization technique for 3D, time-varying simulation data and for higherdimensional data in general. Though conceptually simple, there are several different challenges when realizing glyph rendering on top of triangle rasterization APIs, such as possibly prohibitive polygon counts, limitations of what shapes can be used for the glyphs, issues with visual clutter, etc. In this paper, we investigate the use of hardware ray tracing for high-quality, highperformance glyph rendering, and show that this not only leads to a more flexible and often more elegant solution for dealing with number and shape of glyphs, but that this can also help address visual clutter, and even provide additional visual cues that can enhance understanding of the dataset.
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    Memory-Efficient GPU Volume Path Tracing of AMR Data Using the Dual Mesh
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Zellmann, Stefan; Wu, Qi; Ma, Kwan-Liu; Wald, Ingo; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    A common way to render cell-centric adaptive mesh refinement (AMR) data is to compute the dual mesh and visualize that with a standard unstructured element renderer. While the dual mesh provides a high-quality interpolator, the memory requirements of the dual mesh data structure are significantly higher than those of the original grid, which prevents rendering very large data sets. We introduce a GPU-friendly data structure and a clustering algorithm that allow for efficient AMR dual mesh rendering with a competitive memory footprint. Fundamentally, any off-the-shelf unstructured element renderer running on GPUs could be extended to support our data structure just by adding a gridlet element type in addition to the standard tetrahedra, pyramids, wedges, and hexahedra supported by default. We integrated the data structure into a volumetric path tracer to compare it to various state-of-the-art unstructured element sampling methods. We show that our data structure easily competes with these methods in terms of rendering performance, but is much more memory-efficient.
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    Remote Volume Rendering with a Decoupled, Ray-Traced Display Phase
    (The Eurographics Association, 2021) Zellmann, Stefan; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    We propose an image warping-based remote rendering technique for volumes that decouples the rendering and display phases. For that we build on prior work where we sample the volume on the client using ray casting and reconstruct z-values based on heuristics. Color and depth buffers are then sent to the client, which reuses this depth image as a stand-in for subsequent frames by warping it to reflect the current camera position and orientation until new data was received from the server. The extension we propose in this work represents the depth pixels as spheres and ray traces them on the client side. In contrast to the reference method, this representation adapts the footprint of the depth pixels to the distance to the camera origin, which is more effective at hiding warping artifacts, particularly when applied to volumetric data sets.
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    State-of-the-art in Large-Scale Volume Visualization Beyond Structured Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Sarton, Jonathan; Zellmann, Stefan; Demirci, Serkan; Güdükbay, Ugur; Alexandre-Barff, Welcome; Lucas, Laurent; Dischler, Jean-Michel; Wesner, Stefan; Wald, Ingo; Bruckner, Stefan; Raidou, Renata G.; Turkay, Cagatay
    Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state-of-the-art report, we review works focusing on largescale volume rendering beyond those typical structured and regular grid representations.We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out-of-core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever-increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large-scale volume rendering systems and also include a review of tools that support the various volume data types discussed.
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    Using Hardware Ray Transforms to Accelerate Ray/Primitive Intersections for Long, Thin Primitive Types
    (ACM, 2020) Wald, Ingo; Morrical, Nate; Zellmann, Stefan; Ma, Lei; Usher, Will; Huang, Tiejun; Pascucci, Valerio; Yuksel, Cem and Membarth, Richard and Zordan, Victor
    With the recent addition of hardware ray tracing capabilities, GPUs have become incredibly efficient at ray tracing both triangular geometry, and instances thereof. However, the bounding volume hierarchies that current ray tracing hardware relies on are known to struggle with long, thin primitives like cylinders and curves, because the axis-aligned bounding boxes that these hierarchies rely on cannot tightly bound such primitives. In this paper, we evaluate the use of RTX ray tracing capabilities to accelerate these primitives by tricking the GPU's instancing units into executing a hardware-accelerated oriented bounding box (OBB) rejection test before calling the user's intersection program. We show that this can be done with minimal changes to the intersection programs and demonstrate speedups of up to 5.9× on a variety of data sets.