Analysis of the Path Tracing rendering method on CPU and GPU

Fa molts anys que es realitza recerca al camp de la renderització realista. Tenim diversos mètodes capaços d'aconseguir imatges amb un gran grau de realisme, com pot ser Ray Tracing, Path Tracing, Photon Mapping o Metropolis Light Transport. A excepció del Ray Tracing, la resta de mètodes tracten de resoldre l'Equació de Renderitzat mitjançant aproximacions (és impossible calcular-la íntegrament, ja que necessitaríem temps i potència de càlcul infinita). Gràcies a poder aproximar aquesta equació es poden aconseguir efectes de forma natural, sense necessitat d'un postprocessat, com motion blur, depth of field, càustiques, etc. El mètode que implementarem i estudiarem és el Path Tracing. Realitzarem diverses versions d'aquest mètode amb les quals podrem explorar quina arquitectura (GPU o CPU) ens ofereix una major avantatge pel que fa al rendiment per al nostre algoritme. Per això comptarem amb diverses màquines, una amb un hardware d'última generació, una amb un hardware més econòmic i una última màquina pensada per un entorn professional. És molt usual que les aplicacions que implementen aquest mètode s'utilitzen d'estructures de dades que permeten millorar de forma molt notable el rendiment d'aquesta. Per aquesta raó, implementarem una Bounding Volume Hierarchy, un estructura de tipus arbre, per a la representació de l'escena i així augmentar el rendiment. Estudiarem com recorre-la de dues formes diferents, una recursiva molt més natural en aquest tipus d'estructures i un altre iterativa, per veure com afecta al rendiment de l'aplicació en la GPU. És ben sabut que les funcions recursives no són gens òptimes a la GPU. Per últim, implementarem un seguit de filtres d'eliminació de soroll. El mètode de Path Tracing produeix imatges molt sorolloses si s'utilitzen poques mostres per píxel, per això l'ús de filtres d'eliminació de soroll és molt comú. Això ens permetrà trobar un equilibri entre el nombre de mostres per píxel i la necessitat d'un postfiltratge de la imatge resultant.The field of realistic rendering has been investigated for many years. We have different methods capable of creating images with a high degree of realism, such as Ray Tracing, Path Tracing, Photon Mapping or Metropolis Light Transport. Except for Ray Tracing, the rest of the cited methods try to solve the Rendering Equation by approximations (it is impossible to calculate it completely because we would need time and infinite computing power). Thanks to being able to approximate this equation, effects can be achieved naturally, without needing any post-processing, such as motion blur, depth of field, caustics, etc. The method that we will implement and study is Path Tracing. We will make several versions of this method with which we will explore which architecture (GPU or CPU) gives us a greater advantage in terms of performance for our algorithm. For this, we will have different machines, one with the last generation hardware, one with cheaper hardware and the last machine with hardware thought for a professional environment. It is very usual that the applications that implement this method are assisted by accelerating structures that allow improving in a very notable way the performance of this one. For this same reason, we will implement a Bounding Volume Hierarchy, a tree-type structure, to represent our scene and thus increase performance. We will study how to go through it in two different ways, one recursive much more natural in this type of structure and another iterative, to see how it affects the performance of the application on the GPU. It's well known that the GPU is not optimal for recursive functions. Finally, we'll implement a set of denoising filters. Path tracing produces very noisy images when using a few samples per pixel, so the use of denoising filters is very common. This will also help us find a balance between the number of samples per pixel and the need for post-filtering of the output image

Fast processing of grid maps using graphical multiprocessors

Grid mapping is a very common technique used in mobile robotics to build a continuous 2D representation of the environment useful for navigation purposes. Although its computation is quite simple and fast, this algorithm uses the hypothesis of a known robot pose. In practice, this can require the re-computation of the map when the estimated robot poses change, as when a loop closure is detected. This paper presents a parallelization of a reference implementation of the grid mapping algorithm, which is suitable to be fully run on a graphics card showing huge processing speedups (up to 50×) while fully releasing the main processor, which can be very useful for many Simultaneous Localization and Mapping algorithms

Iterative Methods for Visualization of Implicit Surfaces on GPU

The original publication is available at www.springerlink.comInternational audienceThe ray-casting of implicit surfaces on GPU has been explored in the last few years. However, until recently, they were restricted to second degree (quadrics). We present an iterative solution to ray cast cubics and quartics on GPU. Our solution targets efficient implementation, obtaining interactive rendering for thousands of surfaces per frame. We have given special attention to torus rendering since it is a useful shape for multiple CAD models. We have tested four different iterative methods, including a novel one, comparing them with classical tessellation solution

Interactive ray shading of FRep objects

In this paper we present a method for interactive rendering general procedurally defined functionally represented (FRep) objects using the acceleration with graphics hardware, namely Graphics Processing Units (GPU). We obtain interactive rates by using GPU acceleration for all computations in rendering algorithm, such as ray-surface intersection, function evaluation and normal computations. We compute primary rays as well as secondary rays for shadows, reflection and refraction for obtaining high quality of the output visualization and further extension to ray-tracing of FRep objects. The algorithm is well-suited for modern GPUs and provides acceptable interactive rates with good quality of the results. A wide range of objects can be rendered including traditional skeletal implicit surfaces, constructive solids, and purely procedural objects such as 3D fractals

Otimização em GPU de bounding volume hierarchies para ray tracing

Orientador: Hélio PedriniDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Métodos de Ray Tracing são conhecidos por produzir imagens extremamente realistas ao custo de um alto esforço computacional. Pouco após terem surgido, percebeu-se que a maior parte do custo associado a estes métodos está relacionada a encontrar a intersecção entre o grande número de raios que precisam ser traçados e a geometria da cena. Estruturas de dados especiais que indexam e organizam a geometria foram propostas para acelerar estes cálculos, de forma que apenas um subconjunto da geometria precise ser verificado para encontrar as intersecções. Dentre elas, podemos destacar as Bounding Volume Hierarchies (BVH), que são estruturas usadas para agrupar objetos 3D hierarquicamente. Recentemente, uma grande quantidade de esforços foi aplicada para acelerar a construção destas estruturas e aumentar sua qualidade. Este trabalho apresenta um novo método para a construção de BVHs de alta qualidade em sistemas manycore. O método em questão é uma extensão do atual estado da arte na construção de BVHs em GPU, Treelet Restructuring Bounding Volume Hierarchy (TRBVH), e consiste em otimizar uma árvore já existente reorganizando subconjuntos de seus nós através de uma abordagem de agrupamento aglomerativo. A implementação deste método foi feita para a arquitetura Kepler utilizando CUDA e foi testada em dezesseis cenas que são comumente usadas para avaliar o desempenho de estruturas aceleradoras. É demonstrado que esta implementação é capaz de produzir árvores com qualidade comparável às geradas utilizando TRBVH para aquelas cenas, além de ser 30% mais rápidaAbstract: Ray tracing methods are well known for producing very realistic images at the expense of a high computational effort. Most of the cost associated with those methods comes from finding the intersection between the massive number of rays that need to be traced and the scene geometry. Special data structures were proposed to speed up those calculations by indexing and organizing the geometry so that only a subset of it has to be effectively checked for intersections. One such construct is the Bounding Volume Hierarchy (BVH), which is a tree-like structure used to group 3D objects hierarchically. Recently, a significant amount of effort has been put into accelerating the construction of those structures and increasing their quality. We present a new method for building high-quality BVHs on manycore systems. Our method is an extension of the current state-of-the-art on GPU BVH construction, Treelet Restructuring Bounding Volume Hierarchy (TRBVH), and consists of optimizing an already existing tree by rearranging subsets of its nodes using an agglomerative clustering approach. We implemented our solution for the NVIDIA Kepler architecture using CUDA and tested it on sixteen distinct scenes that are commonly used to evaluate the performance of acceleration structures. We show that our implementation is capable of producing trees whose quality is equivalent to the ones generated by TRBVH for those scenes, while being about 30% faster to do soMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

GPU Cost Estimation for Load Balancing in Parallel Ray Tracing

Interactive ray tracing has seen enormous progress in recent years. However, advanced rendering techniques requiring many million rays per second are still not feasible at interactive speed, and are only possible by means of highly parallel ray tracing. When using compute clusters, good load balancing is crucial in order to fully exploit the available computational power, and to not suffer from the overhead involved by synchronization barriers. In this paper, we present a novel GPU method to compute a costmap: a per-pixel cost estimate of the ray tracing rendering process. We show that the cost map is a powerful tool to improve load balancing in parallel ray tracing, and it can be used for adaptive task partitioning and enhanced dynamic load balancing. Its effectiveness has been proven in a parallel ray tracer implementation tailored for a cluster of workstations