The Hierarchical Ray Engine

Due to the success of texture based approaches, ray casting has lately been confined to performing preprocessing in realtime applications. Though GPU based ray casting implementations outperform the CPU now, they either do not scale well for higher primitive counts, or require the costly construction of spatial hierarchies. We present an improved algorithm based on the Ray Engine approach, which builds a hierarchy of rays instead of objects, completely on the graphics card. Exploiting the coherence between rays when displaying refractive objects or computing caustics, realtime frame rates are achieved without preprocessing. Thus, the method fills a gap in the realtime rendering repertoire

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

The Hierarchical Ray Engine

Due to the success of texture based approaches, ray casting has lately been confined to performing preprocessing in realtime applications. Though GPU based ray casting implementations outperform the CPU now, they either do not scale well for higher primitive counts, or require the costly construction of spatial hierarchies. We present an improved algorithm based on the Ray Engine approach, which builds a hierarchy of rays instead of objects, completely on the graphics card. Exploiting the coherence between rays when displaying refractive objects or computing caustics, realtime frame rates are achieved without preprocessing. Thus, the method fills a gap in the realtime rendering repertoire

Lichttransportsimulation auf Spezialhardware

It cannot be denied that the developments in computer hardware and in computer algorithms strongly influence each other, with new instructions added to help with video processing, encryption, and in many other areas. At the same time, the current cap on single threaded performance and wide availability of multi-threaded processors has increased the focus on parallel algorithms. Both influences are extremely prominent in computer graphics, where the gaming and movie industries always strive for the best possible performance on the current, as well as future, hardware. In this thesis we examine the hardware-algorithm synergies in the context of ray tracing and Monte-Carlo algorithms. First, we focus on the very basic element of all such algorithms - the casting of rays through a scene, and propose a dedicated hardware unit to accelerate this common operation. Then, we examine existing and novel implementations of many Monte-Carlo rendering algorithms on massively parallel hardware, as full hardware utilization is essential for peak performance. Lastly, we present an algorithm for tackling complex interreflections of glossy materials, which is designed to utilize both powerful processing units present in almost all current computers: the Centeral Processing Unit (CPU) and the Graphics Processing Unit (GPU). These three pieces combined show that it is always important to look at hardware-algorithm mapping on all levels of abstraction: instruction, processor, and machine.Zweifelsohne beeinflussen sich Computerhardware und Computeralgorithmen gegenseitig in ihrer Entwicklung: Prozessoren bekommen neue Instruktionen, um zum Beispiel Videoverarbeitung, Verschlüsselung oder andere Anwendungen zu beschleunigen. Gleichzeitig verstärkt sich der Fokus auf parallele Algorithmen, bedingt durch die limitierte Leistung von für einzelne Threads und die inzwischen breite Verfügbarkeit von multi-threaded Prozessoren. Beide Einflüsse sind im Grafikbereich besonders stark , wo es z.B. für die Spiele- und Filmindustrie wichtig ist, die bestmögliche Leistung zu erreichen, sowohl auf derzeitiger und zukünftiger Hardware. In Rahmen dieser Arbeit untersuchen wir die Synergie von Hardware und Algorithmen anhand von Ray-Tracing- und Monte-Carlo-Algorithmen. Zuerst betrachten wir einen grundlegenden Hardware-Bausteins für alle diese Algorithmen, die Strahlenverfolgung in einer Szene, und präsentieren eine spezielle Hardware-Einheit zur deren Beschleunigung. Anschließend untersuchen wir existierende und neue Implementierungen verschiedener MonteCarlo-Algorithmen auf massiv-paralleler Hardware, wobei die maximale Auslastung der Hardware im Fokus steht. Abschließend stellen wir dann einen Algorithmus zur Berechnung von komplexen Beleuchtungseffekten bei glänzenden Materialien vor, der versucht, die heute fast überall vorhandene Kombination aus Hauptprozessor (CPU) und Grafikprozessor (GPU) optimal auszunutzen. Zusammen zeigen diese drei Aspekte der Arbeit, wie wichtig es ist, Hardware und Algorithmen auf allen Ebenen gleichzeitig zu betrachten: Auf den Ebenen einzelner Instruktionen, eines Prozessors bzw. eines gesamten Systems

Hardware-Accelerated SAR Simulation with NVIDIA-RTX Technology

Synthetic Aperture Radar (SAR) is a critical sensing technology that is notably independent of the sensor-to-target distance and has numerous cross-cutting applications, e.g., target recognition, mapping, surveillance, oceanography, geology, forestry (biomass, deforestation), disaster monitoring (volcano eruptions, oil spills, flooding), and infrastructure tracking (urban growth, structure mapping). SAR uses a high-power antenna to illuminate target locations with electromagnetic radiation, e.g., 10GHz radio waves, and illuminated surface backscatter is sensed by the antenna which is then used to generate images of structures. Real SAR data is difficult and costly to produce and, for research, lacks a reliable source ground truth. This article proposes a open source SAR simulator to compute phase histories for arbitrary 3D scenes using newly available ray-tracing hardware made available commercially through the NVIDIA's RTX graphics cards series. The OptiX GPU ray tracing library for NVIDIA GPUs is used to calculate SAR phase histories at unprecedented computational speeds. The simulation results are validated against existing SAR simulation code for spotlight SAR illumination of point targets. The computational performance of this approach provides orders of magnitude speed increases over CPU simulation. An additional order of magnitude of GPU acceleration when simulations are run on RTX GPUs which include hardware specifically to accelerate OptiX ray tracing. The article describes the OptiX simulator structure, processing framework and calculations that afford execution on massively parallel GPU computation device. The shortcoming of the OptiX library's restriction to single precision float representation is discussed and modifications of sensitive calculations are proposed to reduce truncation error thereby increasing the simulation accuracy under this constraint.Comment: 17 pages, 7 figures, Algorithms for Synthetic Aperture Radar Imagery XXVII, SPIE Defense + Commercial Sensing 202

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

Developing and testing algorithms for autonomous vehicles in real world is an expensive and time consuming process. Also, in order to utilize recent advances in machine intelligence and deep learning we need to collect a large amount of annotated training data in a variety of conditions and environments. We present a new simulator built on Unreal Engine that offers physically and visually realistic simulations for both of these goals. Our simulator includes a physics engine that can operate at a high frequency for real-time hardware-in-the-loop (HITL) simulations with support for popular protocols (e.g. MavLink). The simulator is designed from the ground up to be extensible to accommodate new types of vehicles, hardware platforms and software protocols. In addition, the modular design enables various components to be easily usable independently in other projects. We demonstrate the simulator by first implementing a quadrotor as an autonomous vehicle and then experimentally comparing the software components with real-world flights.Comment: Accepted for Field and Service Robotics conference 2017 (FSR 2017

The Iray Light Transport Simulation and Rendering System

While ray tracing has become increasingly common and path tracing is well understood by now, a major challenge lies in crafting an easy-to-use and efficient system implementing these technologies. Following a purely physically-based paradigm while still allowing for artistic workflows, the Iray light transport simulation and rendering system allows for rendering complex scenes by the push of a button and thus makes accurate light transport simulation widely available. In this document we discuss the challenges and implementation choices that follow from our primary design decisions, demonstrating that such a rendering system can be made a practical, scalable, and efficient real-world application that has been adopted by various companies across many fields and is in use by many industry professionals today