EUROGRAPHICS 2015 / O. Sorkine-Hornung and M. Wimmer Volume 34 (2015), Number 2 (Guest Editors) T-SAH: Animation Optimized Bounding Volume Hierarchies J. Bittner and D. Meister Czech Technical University in Prague, Faculty of Electrical Engineering 1.1x vs SAH+refit 5.4x vs SAH+refit 1.3x vs SAH+refit 1.4x vs SAH+refit 1.5x vs HLBVH 1.1x vs HLBVH 2.6x vs HLBVH 1.6x vs HLBVH Figure 1: Average speedups of ray tracing for several tested animations when using our single T-SAH optimized BVH with refitting compared to SAH with refitting and per frame rebuilding using HLBVH algorithm. From left to right: Fairy Forest, Dragon Bunny, San Miguel + Running Horses, Breaking Lion. Abstract We propose a method for creating a bounding volume hierarchy (BVH) that is optimized for all frames of a given animated scene. The method is based on a novel extension of surface area heuristic to temporal domain (T-SAH). We perform iterative BVH optimization using T-SAH and create a single BVH accounting for scene geometry distribution at different frames of the animation. Having a single optimized BVH for the whole animation makes our method extremely easy to integrate to any application using BVHs, limiting the per-frame overhead only to refitting the bounding volumes. We evaluated the T-SAH optimized BVHs in the scope of real-time GPU ray tracing. We demonstrate, that our method can handle even highly complex inputs with large deformations and significant topology changes. The results show, that in a vast majority of tested scenes our method provides significantly better run-time performance than traditional SAH and also better performance than GPU based per-frame BVH rebuild. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Raytracing—I.3.5 [Com- puter Graphics]: Object Hierarchies—I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism— 1. Introduction A number of efficient techniques have been proposed for bounding volume hierarchies. For example methods for con- Ray tracing stands at the core of many rendering algorithms. struction of high quality BVHs [WBKP08, BHH13, KA13, With the advances of computational power it is possible to GHFB13] are particularly suitable for offline applications use ray tracing for interactive applications, including those as they provide hierarchies leading to the best possible ray involving dynamic or animated scenes. Bounding Volume tracing performance. Other class of techniques uses very Hierarchies became a very popular data structure for ray fast BVH construction targeting at interactive and real-time tracing. They exhibit a predictable memory budget, fast con- applications with dynamic and animated scenes [GPM11, struction, very good ray tracing performance, and also allow Kar12]. These methods lead to real-time or interactive per- easy updates for handling dynamic scenes. formance for scenes of low to moderate complexity. c 2015 The Author(s) Computer Graphics Forum c 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. J. Bittner & D. Meister / T-SAH: Animation Optimized Bounding Volume Hierarchies In many cases animated or deformable models exhibit using a 3D space-filling curve. Wald [Wal12] studied the large amount of coherence and just refitting the BVH and possibility of fast rebuilds from scratch on an Intel archi- keeping its topology provides a very good overall perfor- tecture with many cores. Pantaleoni and Luebke [PL10], mance. However, in some cases this approach breaks due to Garanzha et al. [GPM11], and Karras [Kar12] proposed topology changes or large deformations [WBS07]. Several GPU based methods for efficient parallel BVH construction. methods have been proposed to handle this issue by dynam- These techniques achieve impressive performance, but gen- ically updating the BVH at runtime [LYTM06,KIS ∗12]. We erally construct a BVH of lower quality than the full SAH propose to use a novel approach based on temporal extension builders. We use the HLBVH method [GPM11] as one of of the surface area heuristic (T-SAH). We describe an algo- the references for our comparisons. rithm that uses T-SAH to construct a single BVH optimized for a given animation sequence. In the most of the test cases High quality BVH Recently more interest has been de- the T-SAH based BVH provides surprisingly stable results voted to methods, which are not limited to the top-down even for scenes involving very complex topology changes BVH construction. Walter et al. [WBKP08] proposed to use (see the accompanying paper video or snapshots in Figures5 bottom-up agglomerative clustering for constructing a high and6 for the range of topology changes we aim to handle). quality BVH. Gu et al. [GHFB13] proposed a parallel ap- Apart from animated scenes the method can also handle de- proximative agglomerative clustering for accelerating the formable and/or articulated objects such as animated charac- bottom-up BVH construction. Kensler [Ken08], Bittner et ters. al. [BHH13], and Karras and Aila [KA13] proposed to op- timize the BVH by performing topological modifications of Since the BVH can be optimized for the whole anima- the existing tree. These approaches allow to decrease the ex- tion sequence in the preprocess, there is no need to rebuild pected cost of a BVH beyond the cost achieved by the tra- the BVH at runtime. Our tests indicate, that for interactive ditional top down approach. Our method uses an extension rendering of complex scenes with known animations this of the insertion based optimization algorithm proposed by leads to significantly better performance than rebuilding the Bittner et al. [BHH13]. BVH at runtime. The savings are not only due to faster up- date time, but the measured ray tracing performance is also Dynamic and animated scenes Wald et al. [WBS03] sug- higher for most tested scenes, since the preprocess allows to gested to decompose dynamic scenes into multiple objects construct BVH of better quality than the methods working at with their local transformations and use a top-level hierar- runtime. chy for organizing these objects. This concept has recently been used within the Embree ray tracer [WWB∗14]. Lauter- bach et al. [LYTM06] proposed to rebuild subtrees if they ex- 2. Related Work hibit significant SAH cost changes. Gunther et al. [GFW∗06] subdivided the model into clusters of coherent movement SAH Bounding volume hierarchies have a long tradition in and used fuzzy kd-trees to describe the residual geometry rendering and collision detection. Kay and Kajiya [KK86] changes. Olsson [Ols07] studied 4D kd-trees focusing on op- designed one of the first BVH construction algorithms us- timzing their performance for rendering motion blur. Wald ing spatial median splits. Goldsmith and Salmon [GS87] et al. [WBS07] proposed to use BVH refitting combined proposed the measure currently known as the surface area with packet based traversal for rendering dynamic scenes. heuristic (SAH), which predicts the efficiency of the hierar- Ize et al. [IWP07] proposed asynchronous BVH reconstruc- chy during the BVH construction. The vast majority of cur- tion and refitting for increasing runtime performance. Up- rently used methods for BVH construction use a top-down dating BVH at runtime using rotations has been proposed approach based on SAH. A particularly popular method is by Yoon et al. [YCM07] and more recently by Kopta et the fast approximate SAH evaluation using binning proposed al. [KIS∗12]. Garanzha [Gar09] precomputes coherent tri- by Havran et al. [HHS06] and Wald et al. [Wal07]. angle clusters using motion prediction in order to accelerate SAH extensions Several extensions of the basic SAH have the BVH construction at runtime. Mora [Mor11] proposed been proposed in the past. Hunt [Hun08] proposed correc- to perform ray tracing without an explicit data structure us- tions of SAH with respect to mailboxing. Fabianowski et ing a divide and conquer algorithm. Ray tracing animated ∗ al. [FFD09] proposed SAH modification for handling scene scenes was surveyed by Wald et al. [WMG 09]. Unlike the interior ray origins. Bittner and Havran proposed to modify previous methods, our method is the first to create a single SAH by including the actual ray distribution [BH09], Felt- ordinary BVH optimized for the whole animation, requiring man et al. [FLF12] extended this idea to shadow rays. Cor- no topology modifications at runtime. rections of the SAH based BVH quality metrics have been The paper is further structured as follows: Section3 recently proposed by Aila et al. [AKL13]. presents an overview of the proposed method, Section4 Parallel BVH construction Another class of meth- introduces the T-SAH cost model, Section5 describes the ods target fast parallel BVH construction. Lauterbach et BVH construction using T-SAH, Section6 presents the re- al. [LGS∗09] proposed a GPU BVH construction algorithm sults and their discussion, and Section7 concludes the paper. c 2015 The Author(s) Computer Graphics Forum c 2015 The Eurographics Association and John Wiley & Sons Ltd. J. Bittner & D. Meister / T-SAH: Animation Optimized Bounding Volume Hierarchies 3. Algorithm Overview 4. T-SAH for Animations Our algorithm starts by resampling the input animation se- The SAH cost is based on expressing the probability of hit- quence into a small number of representative frames. The ting a bounding volume with a random unoccluded ray. Once representative frames provide information about the geome- the ray hits a bounding volume of area S we express the prob- 0 try distribution during the animation. We construct a BVH ability of hitting its child bounding volume S as the ratio of 0 for the first representative frame using a standard sweep surface areas S =S. The SAH cost of the whole BVH can be based algorithm based on SAH. The BVH is then iteratively expressed as a function of time as: optimized using the cost model given by the temporal exten- sion of the surface area heuristic (T-SAH).