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Segmentwise Discrete Wavelet Transform
Průša, Zdeněk ; Vargic,, Radoslav (referee) ; Dr. Peter L. Sndergaard (referee) ; Rajmic, Pavel (advisor)
Dizertační práce se zabývá algoritmy SegDWT pro segmentový výpočet Diskrétní Waveletové Transformace – DWT jedno i vícedimenzionálních dat. Segmentovým výpočtem se rozumí způsob výpočtu waveletové analýzy a syntézy po nezávislých segmentech (blocích) s určitým překryvem tak, že nevznikají blokové artefakty. Analyzující část algoritmu pracuje na principu odstranění přesahu a produkuje vždy část waveletových koeficientů z waveletové transformace celého signálu, které mohou být následně libovolně zpracovány a podrobeny zpětné transformaci. Rekonstruované segmenty jsou pak skládány podle principu přičtení přesahu. Algoritmus SegDWT, ze kterého tato práce vychází, není v současné podobně přímo použitelný pro vícerozměrné signály. Tato práce obsahuje několik jeho modifikací a následné zobecnění pro vícerozměrné signály pomocí principu separability. Kromě toho je v práci představen algoritmus SegLWT, který myšlenku SegDWT přenáší na výpočet waveletové transformace pomocí nekauzálních struktur filtrů typu lifting.
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Fast signal processing
Rychlý, Ivo ; Langerová, Petra (referee) ; Mikulka, Jan (advisor)
Zvětšující se množství dat v moderním zpracování obrazu vyžaduje nový postupy v psaní algoritmů. Největší překážkou pro úspěšné zrychlení algoritmu je paralelizace a následná optimalizace. Programy jako CUDA a OpenCL s modifikovaným programovacím jazykem a rozhraním pomáhají s tímto problémem a otevírají paralelní zpracování širšímu okruhu lidí. V této práci zabývám základy zpracování obrazu a tomu jak paralelizace algoritmů může urychlit zpracování obrazu.
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Client-Server Application Based on CORBA
Majtán, Martin ; Mašek, Jan (referee) ; Karásek, Jan (advisor)
Bachelor thesis deals with client-server applications and software technologies used to implement client-server applications in the Java programming language. The goal of bachelor thesis is the parallelization of genetic algorithm for knapsack problem and create two distributed models for technology CORBA and Hessian. In the teoretical part of the thesis are describes the basic concept of network communication, explanation client-server model of network communication, there are discussed technologies Java RMI, CORBA and Hessian. In the thesis is described the parallel and the distributed model of data processing, genetic algorithm and its use to solve the knapsack problem. In the practical part is created parallel and distributed model of a genetic algorithm for knapsack problem using technology CORBA and Hessian. In the thesis is done comparison of parallel model and distributed models in terms of calculation time. Results of measurement time are displayed in tables.
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Parallelization of Integer Factorization from the View of RSA Breaking
Breitenbacher, Dominik ; Henzl, Martin (referee) ; Homoliak, Ivan (advisor)
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.
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Genetic Algorithms - Implementation of Multiprocessing
Tuleja, Martin ; Ilgner, Petr (referee) ; Oujezský, Václav (advisor)
Genetic algorithms are modern algorithms intended to solve optimization problems. Inspiration originates in evolutionary principles in nature. Parallelization of genetic algorithms provides not only faster processing but also new and better solutions. Parallel genetic algorithms are also closer to real nature than their sequential counterparts. This paper describes the most used models of parallelization of genetic algorithms. Moreover, it provides the design and implementation in programming language Python. Finally, the implementation is verified in several test cases.
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Build Parallelization in Jenkins Environmnent
Lukášová, Michaela ; Zachariášová, Marcela (referee) ; Dolíhal, Luděk (advisor)
The goal of this bachelor's thesis is parallelization of building Codasip Studio, highly automated developement environment. It focuses on parallelization in Jenkins environment. The implemented solution is mainly focused on speeding up the actual build process. The solution uses a number of Jenkins plugins and several shell scripts, which ensures start of compilation, installation or creation of the final package.
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Ray-tracing Using IPP Library
Kukla, Michal ; Havel, Jiří (referee) ; Hradiš, Michal (advisor)
Master thesis is dealing with design and implementation of ray-tracing and path-tracing using IPP library. Theoretical part discusses current trends in acceleration of selected algorithms and also possibilities of parallelization. Design of ray-tracing and path-tracing algorithm and form of parallelization are described in proposal. This part also discusses implementation of adaptive sampling and importance sampling with Monte Carlo method to accelerate path-tracing algorithm. Next part is dealing with particular steps in implementation of selected rendering methods regarding IPP library. Implementation of network interface using Boost library is also discussed. At the end, implemented methods are subjected to performance and quality test. Final product of this thesis is server aplication capable of handling multiple connections which provides visualisation and client application which implements ray-tracing and path-tracing.
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Building kD Tree on GPU
Bajza, Jakub ; Kula, Michal (referee) ; Kobrtek, Jozef (advisor)
This term project addresses the construction of kD tree acceleration structures and parallelization of this construction using GPU. At the beginning, there is an introduction of the reader into CUDA platform for parallel programming. There is a decription of generic principles as well as specific features that will be used in this thesis. Following that the reader is put into the issue of acceleration structures for Ray tracing. These structures are described and the kD tree acceleration structure and its variants are portrayed in detail. After that the analysis of chosen kD tree variant is broken down and the problems and issuse of its parallel implementation are adressed. As a part of implementation discription, there is a short descripton of CPU variant and detailed specifications of the CUDA kernels. The testing section brings the results of implementation in form of CPU vs GPU comparison, as well as evaluation of how much the metric set in design was fulfilled. In the end there is a summary of achieved goals and results followed by possible future improvements for the implementation.
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