Bounding Volume Hierarchy Construction Research Articles

Parallel Reinsertion for Bounding Volume Hierarchy Optimization

AbstractWe present a novel highly parallel method for optimizing bounding volume hierarchies (BVH) targeting contemporary GPU architectures. The core of our method is based on the insertion‐based BVH optimization that is known to achieve excellent results in terms of the SAH cost. The original algorithm is, however, inherently sequential: no efficient parallel version of the method exists, which limits its practical utility. We reformulate the algorithm while exploiting the observation that there is no need to remove the nodes from the BVH prior to finding their optimized positions in the tree. We can search for the optimized positions for all nodes in parallel while simultaneously tracking the corresponding SAH cost reduction. We update in parallel all nodes for which better position was found while efficiently handling potential conflicts during these updates. We implemented our algorithm in CUDA and evaluated the resulting BVH in the context of the GPU ray tracing. The results indicate that the method is able to achieve the best ray traversal performance among the state of the art GPU‐based BVH construction methods.

Bounding Volume Hierarchy Construction Algorithm Based on Dynamic Task Scheduling

Bounding Volume Hierarchy Construction Algorithm Based on Dynamic Task Scheduling

Parallel Locally-Ordered Clustering for Bounding Volume Hierarchy Construction.

We propose a novel massively parallel construction algorithm for Bounding Volume Hierarchies (BVHs) based on locally-ordered agglomerative clustering. Our method builds the BVH iteratively from bottom to top by merging a batch of cluster pairs in each iteration. To efficiently find the neighboring clusters, we keep the clusters ordered along the Morton curve. This ordering allows us to identify approximate nearest neighbors very efficiently and in parallel. We implemented our algorithm in CUDA and evaluated it in the context of GPU ray tracing. For complex scenes, our method achieves up to a twofold reduction of build times while providing up to 17 percent faster trace times compared with the state-of-the-art methods.

Construction of bounding volume hierarchies with SAH cost approximation on temporary subtrees

Advances in research on quality metrics for bounding volume hierarchies (BVHs) have shown that greedy top-down SAH builders construct BVHs with superior traversal performance despite the fact that the resulting SAH values are higher than those created by more sophisticated builders. Motivated by this observation we examine three construction algorithms that use recursive SAH values of temporarily constructed SAH-built BVHs to guide the construction and perform an extensive evaluation. The resulting BVHs achieve up to 37% better trace performance for primary rays and up to 32% better trace performance for secondary diffuse rays compared to standard plane sweeping without applying spatial splits. Allowing spatial splits still achieves up to 18% resp.15% better performance. While our approach is not suitable for real-time BVH construction, we show that the proposed algorithm has subquadratic computational complexity in the number of primitives, which renders it usable in practical applications. Additionally, we describe an approach for improving the forecasting abilities of the SAH-EPO ray tracing performance predictor which also increases its relevance for primary rays.

Incremental BVH construction for ray tracing

We propose a new method for incremental construction of Bounding Volume Hierarchies (BVHs). Despite the wide belief that the incremental construction of BVH is inefficient we show that our method incrementally constructs a BVH with quality comparable to the best SAH builders. We illustrate the versatility of the proposed method using a flexible parallelization scheme that opens new possibilities for combining different BVH construction heuristics. We demonstrate the usage of the method in a proof-of-concept application for real-time preview of data streamed over the network. We believe that our method will renew the interest in incremental BVH construction and it will find its applications in ray tracing based remote visualizations and fast previews or in interactive scene editing applications handling very large data sets.

Dual graph partitioning for Bottom-Up BVH construction

Bounding Volume Hierarchies (BVHs) are essential tools in performing collision detection on three-dimensional information. They reduce the number of expensive calculations required to determine whether or not two geometrical entities collide by using inexpensive calculations to rule out parts of the objects that could not possibly intersect. Quickly producing a high quality BVH is an important aspect of three-dimensional multimedia analysis. As such a powerful optimization, efficient and high quality BVHs are still an active area of research. Herein, the authors present a novel BVH representation that reduces the redundancy in the tree structure by allowing a node to contain an arbitrary number of children, as well as compressing non-unique nodes and combining their children. A new partitioning scheme using a graphical representation of the object is also presented to improve the quality of the generated BVH.

Efficient offset trimming for deformable planar curves using a dynamic hierarchy of bounding circular arcs

We present an efficient algorithm for computing a family of trimmed offsets for planar freeform curves under deformation. The algorithm is based on a dynamic bounding volume hierarchy (BVH) for the untrimmed offsets of a given planar curve, which can be generated efficiently using a hierarchy of recursive bisections of the given curve. The proposed algorithm is effective for deformable planar curves. At each time frame, we segment the input curve into monotone spiral pieces (Barton and Elber, 2011), which is the only pre-processing needed for the dynamic BVH construction. To speed up the on-line generation of dynamic BVH, we employ the bounding circular arcs (BCA) of Meek and Walton (1995) that can be computed very efficiently using the position and tangent information at the endpoints of each monotone spiral curve segment. Using several experimental results, we demonstrate the performance improvement of our algorithm over the previous biarc-based algorithm of Kim et al. (2012).

Exact and Adaptive Signed Distance Fields Computation for Rigid and Deformable Models on GPUs.

Most techniques for real-time construction of a signed distance field, whether on a CPU or GPU, involve approximate distances. We use a GPU to build an exact adaptive distance field, constructed from an octree by using the Morton code. We use rectangle-swept spheres to construct a bounding volume hierarchy (BVH) around a triangulated model. To speed up BVH construction, we can use a multi-BVH structure to improve the workload balance between GPU processors. An upper bound on distance to the model provided by the octree itself allows us to reduce the number of BVHs involved in determining the distances from the centers of octree nodes at successively lower levels, prior to an exact distance query involving the remaining BVHs. Distance fields can be constructed 35-64 times as fast as a serial CPU implementation of a similar algorithm, allowing us to simulate a piece of fabric interacting with the Stanford Bunny at 20 frames per second.

PDQ: Parallel Distance Queries for deformable meshes

This paper presents a new algorithm to efficiently maintain Bounding-Volume Hierarchies (BVHs) for fast distance queries with deformable polygon meshes using multi-core architectures. The method involves inflating the bounding volumes in an efficient manner to guarantee the enclosure of the deformable model within the BVH at all times. This is done at low additional computation and memory cost without significantly degrading the quality of the BVH and also in a fashion that allows a simple parallel implementation. Additionally, to facilitate fast queries specifically for deforming meshes, we propose a novel algorithm for the bottom-up construction of BVHs that results in much faster distance queries.

Grid-based SAH BVH construction on a GPU

We present an efficient algorithm for building an adaptive bounding volume hierarchy (BVH) in linear time on commodity graphics hardware using CUDA. BVHs are widely used as an acceleration data str...

Micropolygon ray tracing with defocus and motion blur

We present a micropolygon ray tracing algorithm that is capable of efficiently rendering high quality defocus and motion blur effects. A key component of our algorithm is a BVH (bounding volume hierarchy) based on 4D hyper-trapezoids that project into 3D OBBs (oriented bounding boxes) in spatial dimensions. This acceleration structure is able to provide tight bounding volumes for scene geometries, and is thus efficient in pruning intersection tests during ray traversal. More importantly, it can exploit the natural coherence on the time dimension in motion blurred scenes. The structure can be quickly constructed by utilizing the micropolygon grids generated during micropolygon tessellation. Ray tracing of defocused and motion blurred scenes is efficiently performed by traversing the structure. Both the BVH construction and ray traversal are easily implemented on GPUs and integrated into a GPU-based micropolygon renderer. In our experiments, our ray tracer performs up to an order of magnitude faster than the state-of-art rasterizers while consistently delivering an image quality equivalent to a maximum-quality rasterizer. We also demonstrate that the ray tracing algorithm can be extended to handle a variety of effects, such as secondary ray effects and transparency.

Micropolygon ray tracing with defocus and motion blur

We present a micropolygon ray tracing algorithm that is capable of efficiently rendering high quality defocus and motion blur effects. A key component of our algorithm is a BVH (bounding volume hierarchy) based on 4D hyper-trapezoids that project into 3D OBBs (oriented bounding boxes) in spatial dimensions. This acceleration structure is able to provide tight bounding volumes for scene geometries, and is thus efficient in pruning intersection tests during ray traversal. More importantly, it can exploit the natural coherence on the time dimension in motion blurred scenes. The structure can be quickly constructed by utilizing the micropolygon grids generated during micropolygon tessellation. Ray tracing of defocused and motion blurred scenes is efficiently performed by traversing the structure. Both the BVH construction and ray traversal are easily implemented on GPUs and integrated into a GPU-based micropolygon renderer. In our experiments, our ray tracer performs up to an order of magnitude faster than the state-of-art rasterizers while consistently delivering an image quality equivalent to a maximum-quality rasterizer. We also demonstrate that the ray tracing algorithm can be extended to handle a variety of effects, such as secondary ray effects and transparency.

Fast, parallel, and asynchronous construction of BVHs for ray tracing animated scenes

Recent developments have produced several techniques for interactive ray tracing of dynamic scenes. In particular, bounding volume hierarchies (BVHs) are efficient acceleration structures that handle complex triangle distributions and can accommodate deformable scenes by updating (refitting) the bounding primitive without restructuring the entire tree. Unfortunately, updating only the bounding primitive can result in a degradation of the quality of the BVH, and in some scenes will result in a dramatic deterioration of rendering performance. In this paper, we present three different orthogonal techniques to avoid that deterioration: (a) quickly rebuilding the BVH using a fast, binning-based approach; (b) a parallel variant of that build to better exploit the multi-core architecture of modern CPUs; (c) asynchronously rebuilding the BVH concurrently with rendering and animation, allowing it to scale to even larger models by stretching the (parallel) BVH build over one or more frames. Our approach is particularly targeted toward future many-core architectures, and allows for flexibly allocating how many cores are used for rebuilding vs. how many are used for rendering.