Visualization of Large Non-Trivially Partitioned Unstructured Data with Native Distribution on High-Performance Computing Systems.

Interactively visualizing large finite element simulation data on High-Performance Computing (HPC) systems poses several difficulties. Some of these relate to unstructured data, which, even on a single node, is much more expensive to render compared to structured volume data. Worse yet, in the data parallel rendering context, such data with highly non-convex spatial domain boundaries will cause rays along its silhouette to enter and leave a given rank's domains at different distances. This straddling, in turn, poses challenges for both ray marching, which usually assumes successive elements to share a face, and compositing, which usually assumes a single fragment per pixel per rank. We holistically address these issues using a combination of three inter-operating techniques: first, we use a highly optimized GPU ray marching technique that, given an entry point, can march a ray to its exit point with highperformance by exploiting an exclusive-or (XOR) based compaction scheme. Second, we use hardware-accelerated ray tracing to efficiently find the proper entry points for these marching operations. Third, we use a "deep" compositing scheme to properly handle cases where different ranks' ray segments interleave in depth. We use GPU-to-GPU remote direct memory access (RDMA) to achieve interactive frame rates of 10-15 frames per second and higher for our motivating use case, the Fun3D NASA Mars Lander.

Quick Clusters: A GPU-Parallel Partitioning for Efficient Path Tracing of Unstructured Volumetric Grids.

We propose a simple yet effective method for clustering finite elements to improve preprocessing times and rendering performance of unstructured volumetric grids without requiring auxiliary connectivity data. Rather than building bounding volume hierarchies (BVHs) over individual elements, we sort elements along with a Hilbert curve and aggregate neighboring elements together, improving BVH memory consumption by over an order of magnitude. Then to further reduce memory consumption, we cluster the mesh on the fly into sub-meshes with smaller indices using a series of efficient parallel mesh re-indexing operations. These clusters are then passed to a highly optimized ray tracing API for point containment queries and ray-cluster intersection testing. Each cluster is assigned a maximum extinction value for adaptive sampling, which we rasterize into non-overlapping view-aligned bins allocated along the ray. These maximum extinction bins are then used to guide the placement of samples along the ray during visualization, reducing the number of samples required by multiple orders of magnitude (depending on the dataset), thereby improving overall visualization interactivity. Using our approach, we improve rendering performance over a competitive baseline on the NASA Mars Lander dataset from 6× (1 frame per second (fps) and 1.0 M rays per second (rps) up to now 6 fps and 12.4 M rps, now including volumetric shadows) while simultaneously reducing memory consumption by 3×(33 GB down to 11 GB) and avoiding any offline preprocessing steps, enabling high-quality interactive visualization on consumer graphics cards. Then by utilizing the full 48 GB of an RTX 8000, we improve the performance of Lander by 17 × (1 fps up to 17 fps, 1.0 M rps up to 35.6 M rps).

Accelerating Unstructured Mesh Point Location With RT Cores.

We present a technique that leverages ray tracing hardware available in recent Nvidia RTX GPUs to solve a problem other than classical ray tracing. Specifically, we demonstrate how to use these units to accelerate the point location of general unstructured elements consisting of both planar and bilinear faces. This unstructured mesh point location problem has previously been challenging to accelerate on GPU architectures; yet, the performance of these queries is crucial to many unstructured volume rendering and compute applications. Starting with a CUDA reference method, we describe and evaluate three approaches that reformulate these point queries to incrementally map algorithmic complexity to these new hardware ray tracing units. Each variant replaces the simpler problem of point queries with a more complex one of ray queries. Initial variants exploit ray tracing cores for accelerated BVH traversal, and subsequent variants use ray-triangle intersections and per-face metadata to detect point-in-element intersections. Although these later variants are more algorithmically complex, they are significantly faster than the reference method thanks to hardware acceleration. Using our approach, we improve the performance of an unstructured volume renderer by up to 4× for tetrahedral meshes and up to 15× for general bilinear element meshes, matching, or out-performing state-of-the-art solutions while simultaneously improving on robustness and ease-of-implementation.

A Memory Efficient Encoding for Ray Tracing Large Unstructured Data.

In theory, efficient and high-quality rendering of unstructured data should greatly benefit from modern GPUs, but in practice, GPUs are often limited by the large amount of memory that large meshes require for element representation and for sample reconstruction acceleration structures. We describe a memory-optimized encoding for large unstructured meshes that efficiently encodes both the unstructured mesh and corresponding sample reconstruction acceleration structure, while still allowing for fast random-access sampling as required for rendering. We demonstrate that for large data our encoding allows for rendering even the 2.9 billion element Mars Lander on a single off-the-shelf GPU-and the largest 6.3 billion version on a pair of such GPUs.

Ray Tracing Structured AMR Data Using ExaBricks.

Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however, efficiently rendering such data remains a challenge. We present an efficient approach for volume- and iso-surface ray tracing of Structured AMR data on GPU-equipped workstations, using a combination of two different data structures. Together, these data structures allow a ray tracing based renderer to quickly determine which segments along the ray need to be integrated and at what frequency, while also providing quick access to all data values required for a smooth sample reconstruction kernel. Our method makes use of the RTX ray tracing hardware for surface rendering, ray marching, space skipping, and adaptive sampling; and allows for interactive changes to the transfer function and implicit iso-surfacing thresholds. We demonstrate that our method achieves high performance with little memory overhead, enabling interactive high quality rendering of complex AMR data sets on individual GPU workstations.

Ray Tracing Generalized Tube Primitives: Method and Applications.

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.

CPU Isosurface Ray Tracing of Adaptive Mesh Refinement Data.

Adaptive mesh refinement (AMR) is a key technology for large-scale simulations that allows for adaptively changing the simulation mesh resolution, resulting in significant computational and storage savings. However, visualizing such AMR data poses a significant challenge due to the difficulties introduced by the hierarchical representation when reconstructing continuous field values. In this paper, we detail a comprehensive solution for interactive isosurface rendering of block-structured AMR data. We contribute a novel reconstruction strategy-the octant method-which is continuous, adaptive and simple to implement. Furthermore, we present a generally applicable hybrid implicit isosurface ray-tracing method, which provides better rendering quality and performance than the built-in sampling-based approach in OSPRay. Finally, we integrate our octant method and hybrid isosurface geometry into OSPRay as a module, providing the ability to create high-quality interactive visualizations combining volume and isosurface representations of BS-AMR data. We evaluate the rendering performance, memory consumption and quality of our method on two gigascale block-structured AMR datasets.

Combining Single and Packet-Ray Tracing for Arbitrary Ray Distributions on the Intel MIC Architecture.

Wide-SIMD hardware is power and area efficient, but it is challenging to efficiently map ray tracing algorithms to such hardware especially when the rays are incoherent. The two most commonly used schemes are either packet tracing, or relying on a separate traversal stack for each SIMD lane. Both work great for coherent rays, but suffer when rays are incoherent: The former experiences a dramatic loss of SIMD utilization once rays diverge; the latter requires a large local storage, and generates multiple incoherent streams of memory accesses that present challenges for the memory system. In this paper, we introduce a single-ray tracing scheme for incoherent rays that uses just one traversal stack on 16-wide SIMD hardware. It uses a bounding-volume hierarchy with a branching factor of four as the acceleration structure, exploits four-wide SIMD in each box and primitive intersection test, and uses 16-wide SIMD by always performing four such node or primitive tests in parallel. We then extend this scheme to a hybrid tracing scheme that automatically adapts to varying ray coherence by starting out with a 16-wide packet scheme and switching to the new single-ray scheme as soon as rays diverge. We show that on the Intel Many Integrated Core architecture this hybrid scheme consistently, and over a wide range of scenes and ray distributions, outperforms both packet and single-ray tracing.

Exploring a Boeing 777: ray tracing large-scale CAD data.

Unlike rasterization, which draws and shades triangles individually, ray tracing simulates propagation of light between surfaces in a scene and enables advanced effects such as transparency, shadows, and ambient occlusion--effects not easily accomplished in other massive-model rendering approaches. This article describes the application of ray tracing to several aircraft manufacturing scenarios.

Interactive isosurface ray tracing of time-varying tetrahedral volumes.

We describe a system for interactively rendering isosurfaces of tetrahedral finite-element scalar fields using coherent ray tracing techniques on the CPU. By employing state-of-the art methods in polygonal ray tracing, namely aggressive packet/frustum traversal of a bounding volume hierarchy, we can accomodate large and time-varying unstructured data. In conjunction with this efficiency structure, we introduce a novel technique for intersecting ray packets with tetrahedral primitives. Ray tracing is flexible, allowing for dynamic changes in isovalue and time step, visualization of multiple isosurfaces, shadows, and depth-peeling transparency effects. The resulting system offers the intuitive simplicity of isosurfacing, guaranteed-correct visual results, and ultimately a scalable, dynamic and consistently interactive solution for visualizing unstructured volumes.

A coherent grid traversal approach to visualizing particle-based simulation data.

We present an approach to visualizing particle-based simulation data using interactive ray tracing and describe an algorithmic enhancement that exploits the properties of these data sets to provide highly interactive performance and reduced storage requirements. This algorithm for fast packet-based ray tracing of multilevel grids enables the interactive visualization of large time-varying data sets with millions of particles and incorporates advanced features like soft shadows. We compare the performance of our approach with two recent particle visualization systems: one based on an optimized single ray grid traversal algorithm and the other on programmable graphics hardware. This comparison demonstrates that the new algorithm offers an attractive alternative for interactive particle visualization.

Faster isosurface ray tracing using implicit KD-trees.

The visualization of high-quality isosurfaces at interactive rates is an important tool in many simulation and visualization applications. Today, isosurfaces are most often visualized by extracting a polygonal approximation that is then rendered via graphics hardware or by using a special variant of preintegrated volume rendering. However, these approaches have a number of limitations in terms of the quality of the isosurface, lack of performance for complex data sets, or supported shading models. An alternative isosurface rendering method that does not suffer from these limitations is to directly ray trace the isosurface. However, this approach has been much too slow for interactive applications unless massively parallel shared-memory supercomputers have been used. In this paper, we implement interactive isosurface ray tracing on commodity desktop PCs by building on recent advances in real-time ray tracing of polygonal scenes and using those to improve isosurface ray tracing performance as well. The high performance and scalability of our approach will be demonstrated with several practical examples, including the visualization of highly complex isosurface data sets, the interactive rendering of hybrid polygonal/isosurface scenes, including high-quality ray traced shading effects, and even interactive global illumination on isosurfaces.