Uždengtos geometrijos atrinkimas – tai būdas nustatyti geometriją, kuri yra uždengta su kita geometrija ir dėl to gali būti nevaizduojama, nes neturės jokios įtakos vaizduojamam paveikslui. Tokios geometrijos nevaizdavimas didina vaizdavimo procedūros našumą. Egzistuoja eilė uždengtos geometrijos nustatymo būdų, iš kurių vienas yra hierarchinis uždengtos geometrijos atrinkimo algoritmas. Šiame darbe yra analizuojami uždengtos geometrijos nustatymo būdai bei nagrinėjamos pasirinkto algoritmo veikimo spartinimo galimybės panaudojus DirectCompute technologiją. Ši technologija yra Microsoft DirectX 11 bibliotekų rinkinio dalis, kuri leidžia panaudoti grafinį procesorių bendro pobūdžio skaičiavimams. Darbe iškeltų tikslų pasiekimui yra realizuotos kelios bazinės algoritmo versijos modifikacijos, atliekami modifikuotų versijų veikimo laiko bei įvairių veikimo laiką įtakojančių faktorių tyrimai. Yra aptariami gauti rezultatai bei pateikiamos išvados. / Occlusion culling is a method, which task is to determine geometry occluded with other geometry. Rendering this geometry is useless because it wouldn’t impact rendered picture in any way, so discarding it will improve render time. There are various methods to determine occluded geometry and hierarchical occlusion culling is one of them. This document contains a short summary of these methods, but it’s mainly focused on improving hierarchical occlusion culling algorithm performance by making use of DirectCompute technology. This technology is a part of Microsoft DirectX 11 API, which helps the developer to use graphics processor for general-purpose computation. Main goal is reached by performing in-depth analysis of implemented hierarchical occlusion culling algorithm modifications. This analysis consists of both general performance and various performance-related analyses. Further down the road conclusions and recommendations are given based on performed work and overall results.

The computational capacity of graphics cards for general-purpose computinghave progressed fast over the last decade. A major reason is computational heavycomputer games, where standard of performance and high quality graphics constantlyrise. Another reason is better suitable technologies for programming thegraphics cards. Combined, the product is high raw performance devices andmeans to access that performance. This thesis investigates some of the currenttechnologies for general-purpose computing on graphics processing units. Technologiesare primarily compared by means of benchmarking performance andsecondarily by factors concerning programming and implementation. The choiceof technology can have a large impact on performance. The benchmark applicationfound the difference in execution time of the fastest technology, CUDA, comparedto the slowest, OpenCL, to be twice a factor of two. The benchmark applicationalso found out that the older technologies, OpenGL and DirectX, are competitivewith CUDA and OpenCL in terms of resulting raw performance.

Volume rendering is quite an old concept of representing images, dating back to the 1980's. It is very useful in the medical field for visualizing the results of a computer tomography (CT) and magnet resonance tomography (MRT) in 3D. Apart from these two major applications for volume rendering, there aren’t many other fields of usage accept from tech demos. Volumetric data does not have any limitations to the shape of an object that ordinary meshes can have. A popular way of representing volume data is through an algorithm that is called volume raycasting. There is a big disadvantage with this algorithm, namely that it is computationally heavy for the hardware. However, there have been vast improvements of the graphic cards (GPUs) in recent years and with the first GPU implementation of volume raycasting in 2003, how does this algorithm perform on modern hardware? Can the performance of the algorithm be improved with the introduction of GPGPU (DirectCompute) in Directx 11? The performance results of the basic version and the DirectCompute version was compared in this thesis and revealed significant improvement in performance. Speedup was indeed possible when using DirectCompute to optimize volume raycasting. / Implementation, optimering och prestandamätning av en volume rendering algoritm som heter volume raycasting. Optimeringen är utförd med hjälp av DirectCompute i Directx 11.

Context: Fluid-particle systems are seldom used in games, the apparent performance costs of simulating a fluid-particle system discourages the developer to implement a system of such. The processing power delivered by a modern GPU enables the developer to implement complex particle systems such as fluid-particle systems. Writing efficient fluid-particle systems is the key when striving for real-time fluid-particle simulations with good scalability. Objectives: This thesis ultimately tries to provide the reader with a well-performing and scalable fluid-particle system simulated in real-time using a great number of particles. The fluid-particle system implements two different fluid physics models for diversity and comparison purposes. The fluid-particle system will then be measured for each fluid physics model and provide results to educate the reader on how well the performance of a fluid-particle system might scale with the increase of active particles in the simulation. Finally, a performance comparison of the particle scalability is made by completely excluding the fluid physics calculations and simulate the particles using only gravity as an affecting force to be able to demonstrate how taxing the fluid physics calculations are on the GPU. Methods: The fluid-particle system has been run using different simulation scenarios, where each scenario is defined by the amount of particles being active and the dimensions of our fluid-particle simulation space. The performance results from each scenario has then been saved and put into a collection of results for a given simulation space. Results: The results presented demonstrate how well the fluid-particle system actually scales being run on a modern GPU. The system reached over a million particles while still running at an acceptable frame rate, for both of the fluid physics models. The results also shows that the performance is greatly reduced by simulating the particle system as a fluid-particle one, instead of only running it with gravity applied. Conclusions: With the results presented, we are able to conclude that fluid-particle systems scale well with the number of particles being active, while being run on a modern GPU. There are many optimizations to be done to be able to achieve a well-performing fluid-particle system, when developing fluid-particle system you should be wary of the many performance pitfalls that comes with it. / Vätskebaserade partikelsystem används sällan inom realtidsspel. Dessa system är väldigt prestandakrävande, till den grad att de avskräcker utvecklare från att implementera dem i sina realtidsspel. GPGPU ger utvecklare möjligheten att implementera komplexa partikelsystem, såsom vätskepartikelsystem, och simulera dessa system i realtid. Den här uppsatsen utforskar två olika fysikmodeller som kan användas för vätskesimulering, och sedan utförs det prestandamätningar under varierande omständigheter. Baserat på dessa prestandamätningar så kan slutsatser dras om hur skalbart ett vätskepartikelsystem är, alltså hur prestandan sjunker i förhållande till antalet partiklar i systemet. Slutsatser som dras efter att samtliga mätningar har utförts är att dessa system har en god skalbarhet, men att det finns många prestandafallgropar man måste se upp för när man utvecklar ett vätskepartikelsystem.