Efficient GPU Tree Walks for Effective Distributed N-Body Simulations

N-body problems, such as simulating the motion of stars in a galaxy, are popularly solved using tree codes like Barnes-Hut. ChaNGa is a best-of-breed n-body platform that uses an asymptotically-efficient tree traversal strategy known as a dual-tree walk to quickly determine which bodies need to interact with each other to provide an accurate simulation result. However, this strategy does not work well on GPUs, due to the highly-irregular nature of the dual-tree algorithm. On GPUs, ChaNGa uses a hybrid strategy where the CPU performs the tree walk to determine which bodies interact while the GPU performs the force computation. In this paper, we show that a highly-optimized single-tree walk approach is able to achieve better GPU performance by significantly accelerating the tree walk and reducing CPU/GPU communication. Our experiments show that this new design can achieve a 8.25× speedup over baseline ChaNGa using a one node, one process per node configuration

Faster data structures and graphics hardware techniques for high performance rendering

Computer generated imagery is used in a wide range of disciplines, each with different requirements. As an example, real-time applications such as computer games have completely different restrictions and demands than offline rendering of feature films. A game has to render quickly using only limited resources, yet present visually adequate images. Film and visual effects rendering may not have strict time requirements but are still required to render efficiently utilizing huge render systems with hundreds or even thousands of CPU cores. In real-time rendering, with limited time and hardware resources, it is always important to produce as high rendering quality as possible given the constraints available. The first paper in this thesis presents an analytical hardware model together with a feed-back system that guarantees the highest level of image quality subject to a limited time budget. As graphics processing units grow more powerful, power consumption becomes a critical issue. Smaller handheld devices have only a limited source of energy, their battery, and both small devices and high-end hardware are required to minimize energy consumption not to overheat. The second paper presents experiments and analysis which consider power usage across a range of real-time rendering algorithms and shadow algorithms executed on high-end, integrated and handheld hardware. Computing accurate reflections and refractions effects has long been considered available only in offline rendering where time isn’t a constraint. The third paper presents a hybrid approach, utilizing the speed of real-time rendering algorithms and hardware with the quality of offline methods to render high quality reflections and refractions in real-time. The fourth and fifth paper present improvements in construction time and quality of Bounding Volume Hierarchies (BVH). Building BVHs faster reduces rendering time in offline rendering and brings ray tracing a step closer towards a feasible real-time approach. Bonsai, presented in the fourth paper, constructs BVHs on CPUs faster than contemporary competing algorithms and produces BVHs of a very high quality. Following Bonsai, the fifth paper presents an algorithm that refines BVH construction by allowing triangles to be split. Although splitting triangles increases construction time, it generally allows for higher quality BVHs. The fifth paper introduces a triangle splitting BVH construction approach that builds BVHs with quality on a par with an earlier high quality splitting algorithm. However, the method presented in paper five is several times faster in construction time

GPU High-Performance Framework for PIC-like Simulation Methods Using the Vulkan® Explicit API

Within computational continuum mechanics there exists a large category of simulation methods which operate by tracking Lagrangian particles over an Eulerian background grid. These Lagrangian/Eulerian hybrid methods, descendants of the Particle-In-Cell method (PIC), have proven highly effective at simulating a broad range of materials and mechanics including fluids, solids, granular materials, and plasma. These methods remain an area of active research after several decades, and their applications can be found across scientific, engineering, and entertainment disciplines. This thesis presents a GPU driven PIC-like simulation framework created using the Vulkan® API. Vulkan is a cross-platform and open-standard explicit API for graphics and GPU compute programming. Compared to its predecessors, Vulkan offers lower overhead, support for host parallelism, and finer grain control over both device resources and scheduling. This thesis harnesses those advantages to create a programmable GPU compute pipeline backed by a Vulkan adaptation of the SPgrid data-structure and multi-buffered particle arrays. The CPU host system works asynchronously with the GPU to maximize utilization of both the host and device. The framework is demonstrated to be capable of supporting Particle-in-Cell like simulation methods, making it viable for GPU acceleration of many Lagrangian particle on Eulerian grid hybrid methods. This novel framework is the first of its kind to be created using Vulkan® and to take advantage of GPU sparse memory features for grid sparsity

Inference of Many-Taxon Phylogenies

Phylogenetic trees are tree topologies that represent the evolutionary history of a set of organisms. In this thesis, we address computational challenges related to the analysis of large-scale datasets with Maximum Likelihood based phylogenetic inference. We have approached this using different strategies: reduction of memory requirements, reduction of running time, and reduction of man-hours

Working With Incremental Spatial Data During Parallel (GPU) Computation

Central to many complex systems, spatial actors require an awareness of their local environment to enable behaviours such as communication and navigation. Complex system simulations represent this behaviour with Fixed Radius Near Neighbours (FRNN) search. This algorithm allows actors to store data at spatial locations and then query the data structure to find all data stored within a fixed radius of the search origin. The work within this thesis answers the question: What techniques can be used for improving the performance of FRNN searches during complex system simulations on Graphics Processing Units (GPUs)? It is generally agreed that Uniform Spatial Partitioning (USP) is the most suitable data structure for providing FRNN search on GPUs. However, due to the architectural complexities of GPUs, the performance is constrained such that FRNN search remains one of the most expensive common stages between complex systems models. Existing innovations to USP highlight a need to take advantage of recent GPU advances, reducing the levels of divergence and limiting redundant memory accesses as viable routes to improve the performance of FRNN search. This thesis addresses these with three separate optimisations that can be used simultaneously. Experiments have assessed the impact of optimisations to the general case of FRNN search found within complex system simulations and demonstrated their impact in practice when applied to full complex system models. Results presented show the performance of the construction and query stages of FRNN search can be improved by over 2x and 1.3x respectively. These improvements allow complex system simulations to be executed faster, enabling increases in scale and model complexity

Visualization and inspection of the geometry of particle packings

Gegenstand dieser Dissertation ist die Entwicklung von effizienten Verfahren zur Visualisierung und Inspektion der Geometrie von Partikelmischungen. Um das Verhalten der Simulation für die Partikelmischung besser zu verstehen und zu überwachen, sollten nicht nur die Partikel selbst, sondern auch spezielle von den Partikeln gebildete Bereiche, die den Simulationsfortschritt und die räumliche Verteilung von Hotspots anzeigen können, visualisiert werden können. Dies sollte auch bei großen Packungen mit Millionen von Partikeln zumindest mit einer interaktiven Darstellungsgeschwindigkeit möglich sein. . Da die Simulation auf der Grafikkarte (GPU) durchgeführt wird, sollten die Visualisierungstechniken die Daten des GPU-Speichers vollständig nutzen. Um die Qualität von trockenen Partikelmischungen wie Beton zu verbessern, wurde der Korngrößenverteilung große Aufmerksamkeit gewidmet, die die Raumfüllungsrate hauptsächlich beeinflusst und daher zwei der wichtigsten Eigenschaften des Betons bestimmt: die strukturelle Robustheit und die Haltbarkeit. Anhand der Korngrößenverteilung kann die Raumfüllungsrate durch Computersimulationen bestimmt werden, die analytischen Ansätzen in der Praxis wegen der breiten Größenverteilung der Partikel oft überlegen sind. Eine der weit verbreiteten Simulationsmethoden ist das Collective Rearrangement, bei dem die Partikel zunächst an zufälligen Positionen innerhalb eines Behälters platziert werden. Später werden Überlappungen zwischen Partikeln aufgelöst, indem überlappende Partikel voneinander weggedrückt werden. Durch geschickte Anpassung der Behältergröße während der Simulation, kann die Collective Rearrangement-Methode am Ende eine ziemlich dichte Partikelpackung generieren. Es ist jedoch sehr schwierig, den gesamten Simulationsprozess ohne ein interaktives Visualisierungstool zu optimieren oder dort Fehler zu finden. Ausgehend von der etablierten rasterisierungsbasierten Methode zum Darstellen einer großen Menge von Kugeln, bietet diese Dissertation zunächst schnelle und pixelgenaue Methoden zur neuartigen Visualisierung der Überlappungen und Freiräume zwischen kugelförmigen Partikeln innerhalb eines Behälters.. Die auf Rasterisierung basierenden Verfahren funktionieren gut für kleinere Partikelpackungen bis ca. eine Million Kugeln. Bei größeren Packungen entstehen Probleme durch die lineare Laufzeit und den Speicherverbrauch. Zur Lösung dieses Problems werden neue Methoden mit Hilfe von Raytracing zusammen mit zwei neuen Arten von Bounding-Volume-Hierarchien (BVHs) bereitgestellt. Diese können den Raytracing-Prozess deutlich beschleunigen --- die erste kann die vorhandene Datenstruktur für die Simulation wiederverwenden und die zweite ist speichereffizienter. Beide BVHs nutzen die Idee des Loose Octree und sind die ersten ihrer Art, die die Größe von Primitiven für interaktives Raytracing mit häufig aktualisierten Beschleunigungsdatenstrukturen berücksichtigen. Darüber hinaus können die Visualisierungstechniken in dieser Dissertation auch angepasst werden, um Eigenschaften wie das Volumen bestimmter Bereiche zu berechnen. All diese Visualisierungstechniken werden dann auf den Fall nicht-sphärischer Partikel erweitert, bei denen ein nicht-sphärisches Partikel durch ein starres System von Kugeln angenähert wird, um die vorhandene kugelbasierte Simulation wiederverwenden zu können. Dazu wird auch eine neue GPU-basierte Methode zum effizienten Füllen eines nicht-kugelförmigen Partikels mit polydispersen überlappenden Kugeln vorgestellt, so dass ein Partikel mit weniger Kugeln gefüllt werden kann, ohne die Raumfüllungsrate zu beeinträchtigen. Dies erleichtert sowohl die Simulation als auch die Visualisierung. Basierend auf den Arbeiten in dieser Dissertation können ausgefeiltere Algorithmen entwickelt werden, um großskalige nicht-sphärische Partikelmischungen effizienter zu visualisieren. Weiterhin kann in Zukunft Hardware-Raytracing neuerer Grafikkarten anstelle des in dieser Dissertation eingesetzten Software-Raytracing verwendet werden. Die neuen Techniken können auch als Grundlage für die interaktive Visualisierung anderer partikelbasierter Simulationen verwendet werden, bei denen spezielle Bereiche wie Freiräume oder Überlappungen zwischen Partikeln relevant sind.The aim of this dissertation is to find efficient techniques for visualizing and inspecting the geometry of particle packings. Simulations of such packings are used e.g. in material sciences to predict properties of granular materials. To better understand and supervise the behavior of these simulations, not only the particles themselves but also special areas formed by the particles that can show the progress of the simulation and spatial distribution of hot spots, should be visualized. This should be possible with a frame rate that allows interaction even for large scale packings with millions of particles. Moreover, given the simulation is conducted in the GPU, the visualization techniques should take full use of the data in the GPU memory. To improve the performance of granular materials like concrete, considerable attention has been paid to the particle size distribution, which is the main determinant for the space filling rate and therefore affects two of the most important properties of the concrete: the structural robustness and the durability. Given the particle size distribution, the space filling rate can be determined by computer simulations, which are often superior to analytical approaches due to irregularities of particles and the wide range of size distribution in practice. One of the widely adopted simulation methods is the collective rearrangement, for which particles are first placed at random positions inside a container, later overlaps between particles will be resolved by letting overlapped particles push away from each other to fill empty space in the container. By cleverly adjusting the size of the container according to the process of the simulation, the collective rearrangement method could get a pretty dense particle packing in the end. However, it is very hard to fine-tune or debug the whole simulation process without an interactive visualization tool. Starting from the well-established rasterization-based method to render spheres, this dissertation first provides new fast and pixel-accurate methods to visualize the overlaps and free spaces between spherical particles inside a container. The rasterization-based techniques perform well for small scale particle packings but deteriorate for large scale packings due to the large memory requirements that are hard to be approximated correctly in advance. To address this problem, new methods based on ray tracing are provided along with two new kinds of bounding volume hierarchies (BVHs) to accelerate the ray tracing process --- the first one can reuse the existing data structure for simulation and the second one is more memory efficient. Both BVHs utilize the idea of loose octree and are the first of their kind to consider the size of primitives for interactive ray tracing with frequently updated acceleration structures. Moreover, the visualization techniques provided in this dissertation can also be adjusted to calculate properties such as volumes of the specific areas. All these visualization techniques are then extended to non-spherical particles, where a non-spherical particle is approximated by a rigid system of spheres to reuse the existing simulation. To this end a new GPU-based method is presented to fill a non-spherical particle with polydisperse possibly overlapping spheres efficiently, so that a particle can be filled with fewer spheres without sacrificing the space filling rate. This eases both simulation and visualization. Based on approaches presented in this dissertation, more sophisticated algorithms can be developed to visualize large scale non-spherical particle mixtures more efficiently. Besides, one can try to exploit the hardware ray tracing of more recent graphic cards instead of maintaining the software ray tracing as in this dissertation. The new techniques can also become the basis for interactively visualizing other particle-based simulations, where special areas such as free space or overlaps between particles are of interest

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

GPU-parallelisation of Haar wavelet-based grid resolution adaptation for fast finite volume modelling: application to shallow water flows

Wavelet-based grid resolution adaptation driven by the ‘multiresolution analysis’ (MRA) of the Haar wavelet (HW) allows to devise an adaptive first-order finite volume (FV1) model (HWFV1) that can readily preserve the modelling fidelity of its reference uniform-grid FV1 counterpart. However, the MRA entails an enormous computational effort as it involves ‘encoding’ (coarsening), ‘decoding’ (refining), analysing and traversing modelled data across a deep hierarchy of nested, uniform grids. GPU-parallelisation of the MRA is needed to handle its computational effort, but its algorithmic structure (1) hinders coalesced memory access on the GPU and (2) involves an inherently sequential tree traversal problem. This work redesigns the algorithmic structure of the MRA in order to parallelise it on the GPU, addressing (1) by applying Z-order space-filling curves and (2) by adopting a parallel tree traversal algorithm. This results in a GPU-parallelised HWFV1 model (GPU-HWFV1). GPU-HWFV1 is verified against its CPU predecessor (CPU-HWFV1) and its GPU-parallelised reference uniform-grid counterpart (GPU-FV1) over five shallow water flow test cases. GPU-HWFV1 preserves the modelling fidelity of GPU-FV1 while being up to 30 times faster. Compared to CPU-HWFV1, it is up to 200 times faster, suggesting that the GPU-parallelised MRA could be used to speed up other FV1 models

Doctor of Philosophy in Computer Science

dissertationRay tracing is becoming more widely adopted in offline rendering systems due to its natural support for high quality lighting. Since quality is also a concern in most real time systems, we believe ray tracing would be a welcome change in the real time world, but is avoided due to insufficient performance. Since power consumption is one of the primary factors limiting the increase of processor performance, it must be addressed as a foremost concern in any future ray tracing system designs. This will require cooperating advances in both algorithms and architecture. In this dissertation I study ray tracing system designs from a data movement perspective, targeting the various memory resources that are the primary consumer of power on a modern processor. The result is high performance, low energy ray tracing architectures

Foundations and Methods for GPU based Image Synthesis

Effects such as global illumination, caustics, defocus and motion blur are an integral part of generating images that are perceived as realistic pictures and cannot be distinguished from photographs. In general, two different approaches exist to render images: ray tracing and rasterization. Ray tracing is a widely used technique for production quality rendering of images. The image quality and physical correctness are more important than the time needed for rendering. Generating these effects is a very compute and memory intensive process and can take minutes to hours for a single camera shot. Rasterization on the other hand is used to render images if real-time constraints have to be met (e.g. computer games). Often specialized algorithms are used to approximate these complex effects to achieve plausible results while sacrificing image quality for performance. This thesis is split into two parts. In the first part we look at algorithms and load-balancing schemes for general purpose computing on graphics processing units (GPUs). Most of the ray tracing related algorithms (e.g. KD-tree construction or bidirectional path tracing) have unpredictable memory requirements. Dynamic memory allocation on GPUs suffers from global synchronization required to keep the state of current allocations. We present a method to reduce this overhead on massively parallel hardware architectures. In particular, we merge small parallel allocation requests from different threads that can occur while exploiting SIMD style parallelism. We speed-up the dynamic allocation using a set of constraints that can be applied to a large class of parallel algorithms. To achieve the image quality needed for feature films GPU-cluster are often used to cope with the amount of computation needed. We present a framework that employs a dynamic load balancing approach and applies fair scheduling to minimize the average execution time of spawned computational tasks. The load balancing capabilities are shown by handling irregular workloads: a bidirectional path tracer allowing renderings of complex effects at near interactive frame rates. In the second part of the thesis we try to reduce the image quality gap between production and real-time rendering. Therefore, an adaptive acceleration structure for screen-space ray tracing is presented that represents the scene geometry by planar approximations. The benefit is a fast method to skip empty space and compute exact intersection points based on the planar approximation. This technique allows simulating complex phenomena including depth-of-field rendering and ray traced reflections at real-time frame rates. To handle motion blur in combination with transparent objects we present a unified rendering approach that decouples space and time sampling. Thereby, we can achieve interactive frame rates by reusing fragments during the sampling step. The scene geometry that is potentially visible at any point in time for the duration of a frame is rendered in a rasterization step and stored in temporally varying fragments. We perform spatial sampling to determine all temporally varying fragments that intersect with a specific viewing ray at any point in time. Viewing rays can be sampled according to the lens uv-sampling to incorporate depth-of-field. In a final temporal sampling step, we evaluate the pre-determined viewing ray/fragment intersections for one or multiple points in time. This allows incorporating standard shading effects including and resulting in a physically plausible motion and defocus blur for transparent and opaque objects