Evaluating the Performance of Vulkan GLSL Compute Shaders in Real-Time Ray-Traced Audio Propagation Through 3D Virtual Environments

Real time ray tracing is a growing area of interest with applications in audio processing. However, real time audio processing comes with strict performance requirements, which parallel computing is often used to overcome. As graphics processing units (GPUs) have become more powerful and programmable, general-purpose computing on graphics processing units (GPGPU) has allowed GPUs to become extremely powerful parallel processors, leading them to become more prevalent in the domain of audio processing through platforms such as CUDA. The aim of this research was to investigate the potential of GLSL compute shaders in the domain of real time audio processing. Specifically regarding real time ray tracing tasks. To do this a number of GLSL compute shaders were created, along with a C++ Vulkan application with which to execute them. These shaders facilitate the propagation of audio, using ray tracing, through a virtual environment, and implement 3D space partitioning and ray intersection prediction in order to gauge the effectiveness of these optimisations for this task. Statistically significant results show that the GLSL compute shaders successfully propagated audio through a virtual environment, returning results to the host system in real time, within 30 milliseconds. However, while this capability was shown, significantly detailed virtual environments prevented results from being returned in real time. Indicating a potential for future research and optimisation

Exploiting Graphics Processing Units for Massively Parallel Multi-Dimensional Indexing

Department of Computer EngineeringScientific applications process truly large amounts of multi-dimensional datasets. To efficiently navigate such datasets, various multi-dimensional indexing structures, such as the R-tree, have been extensively studied for the past couple of decades. Since the GPU has emerged as a new cost-effective performance accelerator, now it is common to leverage the massive parallelism of the GPU in various applications such as medical image processing, computational chemistry, and particle physics. However, hierarchical multi-dimensional indexing structures are inherently not well suited for parallel processing because their irregular memory access patterns make it difficult to exploit massive parallelism. Moreover, recursive tree traversal often fails due to the small run-time stack and cache memory in the GPU. First, we propose Massively Parallel Three-phase Scanning (MPTS) R-tree traversal algorithm to avoid the irregular memory access patterns and recursive tree traversal so that the GPU can access tree nodes in a sequential manner. The experimental study shows that MPTS R-tree traversal algorithm consistently outperforms traditional recursive R-Tree search algorithm for multi-dimensional range query processing. Next, we focus on reducing the query response time and extending n-ary multi-dimensional indexing structures - R-tree, so that a large number of GPU threads cooperate to process a single query in parallel. Because the number of submitted concurrent queries in scientific data analysis applications is relatively smaller than that of enterprise database systems and ray tracing in computer graphics. Hence, we propose a novel variant of R-trees Massively Parallel Hilbert R-Tree (MPHR-Tree), which is designed for a novel parallel tree traversal algorithm Massively Parallel Restart Scanning (MPRS). The MPRS algorithm traverses the MPHR-Tree in mostly contiguous memory access patterns without recursion, which offers more chances to optimize the parallel SIMD algorithm. Our extensive experimental results show that the MPRS algorithm outperforms the other stackless tree traversal algorithms, which are designed for efficient ray tracing in computer graphics community. Furthermore, we develop query co-processing scheme that makes use of both the CPU and GPU. In this approach, we store the internal and leaf nodes of upper tree in CPU host memory and GPU device memory, respectively. We let the CPU traverse internal nodes because the conditional branches in hierarchical tree structures often cause a serious warp divergence problem in the GPU. For leaf nodes, the GPU scans a large number of leaf nodes in parallel based on the selection ratio of a given range query. It is well known that the GPU is superior to the CPU for parallel scanning. The experimental results show that our proposed multi-dimensional range query co-processing scheme improves the query response time by up to 12x and query throughput by up to 4x compared to the state-of-the-art GPU tree traversal algorithm.ope

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

Generating renderers

Most production renderers developed for the film industry are huge pieces of software that are able to render extremely complex scenes. Unfortunately, they are implemented using the currently available programming models that are not well suited to modern computing hardware like CPUs with vector units or GPUs. Thus, they have to deal with the added complexity of expressing parallelism and using hardware features in those models. Since compilers cannot alone optimize and generate efficient programs for any type of hardware, because of the large optimization spaces and the complexity of the underlying compiler problems, programmers have to rely on compiler-specific hardware intrinsics or write non-portable code. The consequence of these limitations is that programmers resort to writing the same code twice when they need to port their algorithm on a different architecture, and that the code itself becomes difficult to maintain, as algorithmic details are buried under hardware details. Thankfully, there are solutions to this problem, taking the form of Domain-Specific Lan- guages. As their name suggests, these languages are tailored for one domain, and compilers can therefore use domain-specific knowledge to optimize algorithms and choose the best execution policy for a given target hardware. In this thesis, we opt for another way of encoding domain- specific knowledge: We implement a generic, high-level, and declarative rendering and traversal library in a functional language, and later refine it for a target machine by providing partial evaluation annotations. The partial evaluator then specializes the entire renderer according to the available knowledge of the scene: Shaders are specialized when their inputs are known, and in general, all redundant computations are eliminated. Our results show that the generated renderers are faster and more portable than renderers written with state-of-the-art competing libraries, and that in comparison, our rendering library requires less implementation effort.Die meisten in der Filmindustrie zum Einsatz kommenden Renderer sind riesige Softwaresysteme, die in der Lage sind, extrem aufwendige Szenen zu rendern. Leider sind diese mit den aktuell verfügbaren Programmiermodellen implementiert, welche nicht gut geeignet sind für moderne Rechenhardware wie CPUs mit Vektoreinheiten oder GPUs. Deshalb müssen Entwickler sich mit der zusätzlichen Komplexität auseinandersetzen, Parallelismus und Hardwarefunktionen in diesen Programmiermodellen auszudrücken. Da Compiler nicht selbständig optimieren und effiziente Programme für jeglichen Typ Hardware generieren können, wegen des großen Optimierungsraumes und der Komplexität des unterliegenden Kompilierungsproblems, müssen Programmierer auf Compiler-spezifische Hardware-“Intrinsics” zurückgreifen, oder nicht portierbaren Code schreiben. Die Konsequenzen dieser Limitierungen sind, dass Programmierer darauf zurückgreifen den gleichen Code zweimal zu schreiben, wenn sie ihre Algorithmen für eine andere Architektur portieren müssen, und dass der Code selbst schwer zu warten wird, da algorithmische Details unter Hardwaredetails verloren gehen. Glücklicherweise gibt es Lösungen für dieses Problem, in der Form von DSLs. Diese Sprachen sind maßgeschneidert für eine Domäne und Compiler können deshalb Domänenspezifisches Wissen nutzen, um Algorithmen zu optimieren und die beste Ausführungsstrategie für eine gegebene Zielhardware zu wählen. In dieser Dissertation wählen wir einen anderen Weg, Domänenspezifisches Wissen zu enkodieren: Wir implementieren eine generische, high-level und deklarative Rendering- und Traversierungsbibliothek in einer funktionalen Programmiersprache, und verfeinern sie später für eine Zielmaschine durch Bereitstellung von Annotationen für die partielle Auswertung. Der “Partial Evaluator” spezialisiert dann den kompletten Renderer, basierend auf dem verfügbaren Wissen über die Szene: Shader werden spezialisiert, wenn ihre Eingaben bekannt sind, und generell werden alle redundanten Berechnungen eliminiert. Unsere Ergebnisse zeigen, dass die generierten Renderer schneller und portierbarer sind, als Renderer geschrieben mit den aktuellen Techniken konkurrierender Bibliotheken und dass, im Vergleich, unsere Rendering Bibliothek weniger Implementierungsaufwand erfordert.This work was supported by the Federal Ministry of Education and Research (BMBF) as part of the Metacca and ProThOS projects as well as by the Intel Visual Computing Institute (IVCI) and Cluster of Excellence on Multimodal Computing and Interaction (MMCI) at Saarland University. Parts of it were also co-funded by the European Union(EU), as part of the Dreamspace project

Sparse Volumetric Deformation

Volume rendering is becoming increasingly popular as applications require realistic solid shape representations with seamless texture mapping and accurate filtering. However rendering sparse volumetric data is difficult because of the limited memory and processing capabilities of current hardware. To address these limitations, the volumetric information can be stored at progressive resolutions in the hierarchical branches of a tree structure, and sampled according to the region of interest. This means that only a partial region of the full dataset is processed, and therefore massive volumetric scenes can be rendered efficiently. The problem with this approach is that it currently only supports static scenes. This is because it is difficult to accurately deform massive amounts of volume elements and reconstruct the scene hierarchy in real-time. Another problem is that deformation operations distort the shape where more than one volume element tries to occupy the same location, and similarly gaps occur where deformation stretches the elements further than one discrete location. It is also challenging to efficiently support sophisticated deformations at hierarchical resolutions, such as character skinning or physically based animation. These types of deformation are expensive and require a control structure (for example a cage or skeleton) that maps to a set of features to accelerate the deformation process. The problems with this technique are that the varying volume hierarchy reflects different feature sizes, and manipulating the features at the original resolution is too expensive; therefore the control structure must also hierarchically capture features according to the varying volumetric resolution. This thesis investigates the area of deforming and rendering massive amounts of dynamic volumetric content. The proposed approach efficiently deforms hierarchical volume elements without introducing artifacts and supports both ray casting and rasterization renderers. This enables light transport to be modeled both accurately and efficiently with applications in the fields of real-time rendering and computer animation. Sophisticated volumetric deformation, including character animation, is also supported in real-time. This is achieved by automatically generating a control skeleton which is mapped to the varying feature resolution of the volume hierarchy. The output deformations are demonstrated in massive dynamic volumetric scenes

Interactive global illumination on the CPU

Computing realistic physically-based global illumination in real-time remains one of the major goals in the fields of rendering and visualisation; one that has not yet been achieved due to its inherent computational complexity. This thesis focuses on CPU-based interactive global illumination approaches with an aim to develop generalisable hardware-agnostic algorithms. Interactive ray tracing is reliant on spatial and cache coherency to achieve interactive rates which conflicts with needs of global illumination solutions which require a large number of incoherent secondary rays to be computed. Methods that reduce the total number of rays that need to be processed, such as Selective rendering, were investigated to determine how best they can be utilised. The impact that selective rendering has on interactive ray tracing was analysed and quantified and two novel global illumination algorithms were developed, with the structured methodology used presented as a framework. Adaptive Inter- leaved Sampling, is a generalisable approach that combines interleaved sampling with an adaptive approach, which uses efficient component-specific adaptive guidance methods to drive the computation. Results of up to 11 frames per second were demonstrated for multiple components including participating media. Temporal Instant Caching, is a caching scheme for accelerating the computation of diffuse interreflections to interactive rates. This approach achieved frame rates exceeding 9 frames per second for the majority of scenes. Validation of the results for both approaches showed little perceptual difference when comparing against a gold-standard path-traced image. Further research into caching led to the development of a new wait-free data access control mechanism for sharing the irradiance cache among multiple rendering threads on a shared memory parallel system. By not serialising accesses to the shared data structure the irradiance values were shared among all the threads without any overhead or contention, when reading and writing simultaneously. This new approach achieved efficiencies between 77% and 92% for 8 threads when calculating static images and animations. This work demonstrates that, due to the flexibility of the CPU, CPU-based algorithms remain a valid and competitive choice for achieving global illumination interactively, and an alternative to the generally brute-force GPU-centric algorithms