Browsing by Author "Wald, Ingo"

Now showing 1 - 13 of 13
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    Compressed-Leaf Bounding Volume Hierarchies
    (ACM, 2018) Benthin, Carsten; Wald, Ingo; Woop, Sven; Áfra, Attila T.; Patney, Anjul and Niessner, Matthias
    We propose and evaluate what we call Compressed-Leaf Bounding Volume Hierarchies (CLBVH), which strike a balance between compressed and non-compressed BVH layouts. Our CLBVH layout introduces dedicated compressed multi-leaf nodes where most effective at reducing memory use, and uses regular BVH nodes for inner nodes and small, isolated leaves. We show that when implemented within the Embree ray tracing framework, this approach achieves roughly the same memory savings as Embree's compressed BVH layout, while maintaining almost the full performance of its fastest non-compressed BVH.
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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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    Data Parallel Path Tracing with Object Hierarchies
    (ACM Association for Computing Machinery, 2022) Wald, Ingo; Parker, Steven G; Josef Spjut; Marc Stamminger; Victor Zordan
    We propose a new approach to rendering production-style content with full path tracing in a data-distributed fashion-that is, with multiple collaborating nodes and/or GPUs that each store only part of the model. In particular, we propose a new approach to ray-forwarding based data-parallel ray tracing that improves over traditional spatial partitioning, that can support both object-hierarchy and spatial partitioning (or any combination thereof), and that employs multiple techniques for reducing the number of rays sent across the network. We show that this approach can simultaneously achieve higher flexibility in model partitioning, lower memory per node, lower bandwidth during rendering, and higher performance; and that it can ultimately achieve interactive rendering performance for non-trivial models with full path tracing even on quite moderate hardware resources with relatively low-end interconnect.
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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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    Ray Tracing Generalized Tube Primitives: Method and Applications
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Han, Mengjiao; Wald, Ingo; Usher, Will; Wu, Qi; Wang, Feng; Pascucci, Valerio; Hansen, Charles D.; Johnson, Chris R.; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    We present a general high-performance technique for ray tracing generalized tube primitives. Our technique efficiently supports tube primitives with fixed and varying radii, general acyclic graph structures with bifurcations, and correct transparency with interior surface removal. Such tube primitives are widely used in scientific visualization to represent diffusion tensor imaging tractographies, neuron morphologies, and scalar or vector fields of 3D flow. We implement our approach within the OSPRay ray tracing framework, and evaluate it on a range of interactive visualization use cases of fixed- and varying-radius streamlines, pathlines, complex neuron morphologies, and brain tractographies. Our proposed approach provides interactive, high-quality rendering, with low memory overhead.
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    RTX Beyond Ray Tracing: Exploring the Use of Hardware Ray Tracing Cores for Tet-Mesh Point Location
    (The Eurographics Association, 2019) Wald, Ingo; Usher, Will; Morrical, Nathan; Lediaev, Laura; Pascucci, Valerio; Steinberger, Markus and Foley, Tim
    We explore a first proof-of-concept example of creatively using the Turing generation's hardware ray tracing cores to solve a problem other than classical ray tracing, specifically, point location in unstructured tetrahedral meshes. Starting with a CUDA reference method, we describe and evaluate three different approaches to reformulate this problem in a manner that allows it to be mapped to these new hardware units. Each variant replaces the simpler problem of point queries with the more complex one of ray queries; however, thanks to hardware acceleration, these approaches are actually faster than the reference method.
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    Scalable Ray Tracing Using the Distributed FrameBuffer
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Usher, Will; Wald, Ingo; Amstutz, Jefferson; Günther, Johannes; Brownlee, Carson; Pascucci, Valerio; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Image- and data-parallel rendering across multiple nodes on high-performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, reducing bottlenecks incurred by the visualization and compositing is of key concern to reduce the overall simulation runtime. Moreover, prior algorithms have been designed to support either image- or data-parallel rendering and impose restrictions on the data distribution, requiring different implementations for each configuration. In this paper, we introduce the Distributed FrameBuffer, an asynchronous image-processing framework for multi-node rendering. We demonstrate that our approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distributions. By building on this framework, we extend the open-source ray tracing library OSPRay with a data-distributed API, enabling its use in data-distributed and in situ visualization applications.
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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.