Browsing by Author "Pascucci, Valerio"

Now showing 1 - 6 of 6
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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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    Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) McDonald, Torin; Shrestha, Rebika; Yi, Xiyu; Bhatia, Harsh; Chen, De; Goswami, Debanjan; Pascucci, Valerio; Turbyville, Thomas; Bremer, Peer-Timo; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Single particle tracking (SPT) of fluorescent molecules provides significant insights into the diffusion and relative motion of tagged proteins and other structures of interest in biology. However, despite the latest advances in high-resolution microscopy, individual particles are typically not distinguished from clusters of particles. This lack of resolution obscures potential evidence for how merging and splitting of particles affect their diffusion and any implications on the biological environment. The particle tracks are typically decomposed into individual segments at observed merge and split events, and analysis is performed without knowing the true count of particles in the resulting segments. Here, we address the challenges in analyzing particle tracks in the context of cancer biology. In particular, we study the tracks of KRAS protein, which is implicated in nearly 20% of all human cancers, and whose clustering and aggregation have been linked to the signaling pathway leading to uncontrolled cell growth. We present a new analysis approach for particle tracks by representing them as tracking graphs and using topological events –- merging and splitting, to disambiguate the tracks. Using this analysis, we infer a lower bound on the count of particles as they cluster and create conditional distributions of diffusion speeds before and after merge and split events. Using thousands of time-steps of simulated and in-vitro SPT data, we demonstrate the efficacy of our method, as it offers the biologists a new, detailed look into the relationship between KRAS clustering and diffusion speeds.
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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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    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.