This diploma thesis deals with acceleration of advanced genetic algorithm. For implementation, discrete and continuos versions of UMDA genetic algorithm were chosen. The main part of the acceleration is the utilization of SSE instruction set. Using this set, the functions for calculating fitness and new population sampling were accelerated in particular. Then the pseudorandom number generator that also uses SSE instruction set was implemented.  The discrete algorithm reached the speed of up to 4,6 after this implementation. Finally, the algorithms were modified so that the system  OpenMP could be used, which enables the running of blocks of code in more threads. The continuous version of algorithm is not convenient for parallelization, because computational complexity of that algorithm is low. In comparison, the discrete versions of algorithm are really appropriate for parallelization. Both the implemented versions reached the total acceleration of up to 4,9 and 7,2.

This thesis aims to explore possible implementations and optimizations of the lattice-Boltzmann method. This method allows modeling of fluid flow using a simulation of fictive particles. The thesis focuses on possible improvements of the existing tool HemeLB which  is designed and optimized for bloodflow modeling. Several vectorization and paralellization approaches that could be included in this tool are explored. An application focused on comparing chosen algorithms including optimizations for the lattice-Boltzmann method was implemented as a part of the thesis. A group of tests focused on comparing this algorithms according to performance, cache usage and overall memory usage was performed. The best performance achieved was 150 millions of lattice site updates per second.

Práce se zaměřuje na efektivní výpočet dvourozměrné diskrétní vlnkové transformace. Současné metody jsou v práci rozšířeny v několika směrech a to tak, aby spočetly tuto transformaci v jediném průchodu, a to případně víceúrovňově, použitím kompaktního jádra. Tohle jádro dále může být vhodně přeorganizováno za účelem minimalizace užití některých prostředků. Představený přístup krásně zapadá do běžně používaných rozšíření SIMD, využívá hierarchii cache pamětí moderních procesorů a je vhodný k paralelnímu výpočtu. Prezentovaný přístup je nakonec začleněn do kompresního řetězce formátu JPEG 2000, ve kterém se ukázal být zásadně rychlejší než široce používané implementace.

In metallurgy it is important to know a cooling efficiency of a product as well as cooling efficiency of working rolls to maximize the quality of the product and to achieve the long life of working rolls. It is possible to examine this cooling efficiency by heat transfer coefficients and surface temperatures. The surface temperature is hardly measured during the cooling. It is better to compute it together with heat transfer coefficient by inverse heat conduction problem. The computation is not easy and it uses estimated values which are verified by direct heat conduction problem. The time-consuming of this task can be several days or weeks, depends on the complexity of the model. Thus there are tendencies to shorten the computational time. This doctoral thesis considers the possible way of the computing time shortening of inverse heat conduction problem, which is the parallelization of this task and its transfer to a graphic card. It has greater computing power than the central processing unit (CPU). One computer can have more compute devices. That is why the computing time on different types of devices is compared in this thesis. Next this thesis deals with obtaining of surface temperatures for the computation by infrared line scanner and using of inverse heat conduction problem for the computing of the surface temperature and heat transfer coefficient during passing of a test sample under cooling section and cooling by high pressure nozzles.

Goal of this work is to write an optimized program for visualization of 3D scenes using ray tracing method. First, the theory of ray tracing together with particular techniques are presented. Next part focuses on different approaches to accelerate the algorithm. These are space partitioning structures, fast ray-triangle intersection technique and possibilities to parallelize the whole ray tracing method. A standalone chapter addresses the design and implementation of the ray tracing program.

This master's thesis addresses processing of flow monitoring records from a point of view of an IPFIX collector. It analysis the current solution of the modular collector, which went through considerable historical development, and focuses on revealing its strengths and weaknesses. Based on acquired knowledge, a new collector is designed. The new solution, which significantly modifies individual components for processing of flow records, focuses on high throughput and adds missing functionalities. The document also compares performance of both generations and the new collector clearly dominates.

This thesis deals with modelling of continuous casting of steel. This process of steel manufacturing has achieved dominant position not only in the Czech Republic but also worldwide. The solved casted bar cross-section shape is circular, because it is rarely studied in academical works nowadays. First part of thesis focuses on creating numerical model of thermal field, using finite difference method with cylindrical coordinates. This model is then employed in optimization part, which represents control problem of abrupt step change of casting speed. The main goal is to find out, whether the computation of numerical model and optimization both can be parallelized using spatial decomposition. To achieve that, Progressive Hedging Algorithm from the field of stochastic optimization has been used.

In metallurgy it is important to know a cooling efficiency of a product as well as cooling efficiency of working rolls to maximize the quality of the product and to achieve the long life of working rolls. It is possible to examine this cooling efficiency by heat transfer coefficients and surface temperatures. The surface temperature is hardly measured during the cooling. It is better to compute it together with heat transfer coefficient by inverse heat conduction problem. The computation is not easy and it uses estimated values which are verified by direct heat conduction problem. The time-consuming of this task can be several days or weeks, depends on the complexity of the model. Thus there are tendencies to shorten the computational time. This doctoral thesis considers the possible way of the computing time shortening of inverse heat conduction problem, which is the parallelization of this task and its transfer to a graphic card. It has greater computing power than the central processing unit (CPU). One computer can have more compute devices. That is why the computing time on different types of devices is compared in this thesis. Next this thesis deals with obtaining of surface temperatures for the computation by infrared line scanner and using of inverse heat conduction problem for the computing of the surface temperature and heat transfer coefficient during passing of a test sample under cooling section and cooling by high pressure nozzles.

This paper follows up the factorization of integers. Factorization is the most popular and used method for RSA cryptoanalysis. The SIQS was chosen as a factorization method that will be used in this paper. Although SIQS is the fastest method (up to 100 digits), it can't be effectively computed at polynomial time, so it's needed to look up for options, how to speed up the method as much as possible. One of the possible ways is paralelization. In this case OpenMP was used. Other possible way is optimalization. The goal of this paper is also to show, how easily is possible to use paralelizion and thanks to detailed analyzation the source codes one can reach relatively large speed up. Used method of iterative optimalization showed itself as a very effective tool. Using this method the implementation of SIQS achieved almost 100 multiplied speed up and at some parts of the code even more.

Generating fully 3D terrains is a dificult task, meaning that we need to store a lot of data or do a lot of computing or both. We can reduce or completly eliminate the data srorage by using a procedural approch, but this is where the problem gets realy computationaly costly and the CUDA platform comes in. CUDA kernels runinng parallely on graphic accelerators can rapidly decrease time needed for computation, allowing even these complex calculations to work in real time or even better. Finding its use in game or movie industry.