The paper describes a theoretical base and realization of realistic volumetric clouds visualization in an environment of real-time simulator. The first part is concerned with a meteorological background of this problem. I show international classification of ten basic cloud types including a short description and cases of occurence. The following part is concerned with an interaction between cloudiness and simulation core, which is based on the fact, that each cloud acts as a mechanical or an electromagnetic obstacle. This should be considered on some way in simulation. The next part describes technologies and practical implementations of visualization and evaluates their characteristics. Finally, the last chapter describes my implementation and tries to outline project advancement.

This thesis deals with simulation and rendering of fluid based volumetric effects, especially effect of fire and smoke. Computations are accelerated on graphics card using modern graphics API with motivation to achieve realistic visual results as well as physically correct calculations. Implemented volumetric effects are distributed as dynamic library which allows addition of these effects to existing applications.

Task of this thesis is creation of real-time simulation of the water waves. It is implemented on Mac OS X platform using OpenGL. This thesis is based on height map surface. Heigh map is computed by suming of sinusoids with complex, time-based amplitudes. Fast Fourier transformation, Phillips spectrum and gauss random generator are used to solve this problem. The thesis is also implemented on iOS platform and optimized to run on mobile devices thanks to using programmable graphic pipeline and other drawing and computing optimizations.

This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. First chapter deeply analyses Genetic algorithms and corresponding topics like population, chromosome, crossover, mutation and selection. Next part of the thesis shows GPU abilities for unified computing using both DirectX/OpenGL with Cg and specialized GPGPU libraries like CUDA. The fourth chapter focuses on design of GPU implementation using CUDA, coarse-grained and fine-grained GAs are discussed, and completed by sorting and random number generation task accelerated by GPU. Next chapter covers implementation details -- migration, crossover and selection schemes mapped on CUDA software model. All GA elements and quality of GPU results are described in the last chapter.