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Simulation of Heat Diffusion in the Brain Using High-Level GPGPU Techniques
Krbila, Martin ; Kadlubiak, Kristián (referee) ; Jaroš, Jiří (advisor)
This master's thesis deals with acceleration of heat diffusion simulation using graphics cards. It describes an approach to acceleration of an existing implementation in Matlab, which is a part of k-Wave package. Various high-level as well as low-level libraries for GPU programming are introduced here and their strengths and weaknesses compared. A complete implementation of the simulation on GPU was created as a part of this work. This implementation achieves around hundredfold speedup over the existing CPU solution in Matlab. A module for computation of discrete trigonometric transformations on graphics card was created to accelerate simulation with various boundary conditions. This module achieves around ten times speedup over the best CPU implementation. Another output of this thesis is a performance comparison of several implementations of basic diffusion simulation each using a different GPGPU technique.
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Parallelisation of Ultrasound Simulations on Multi-GPU Clusters
Dujíček, Aleš ; Kula, Michal (referee) ; Jaroš, Jiří (advisor)
This work is part of the k-Wave project, which is a toolbox designed for time ultrasound simulations in complex and heterogeneous media. The simulation functions are based on the k-space pseudospectral method. The goal of this work is to compute these simulations on graphics cards using local domain decompostion. Thanks to decomposition we could compute these simulations faster, and on larger data grids. The main goal of this work is to achieve efficiency and scalability.
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Exploitation of GPU in graphics and image processing algorithms
Jošth, Radovan ; Svoboda, David (referee) ; Trajtel,, Ľudovít (referee) ; Herout, Adam (advisor)
Táto práca popisuje niekoľko vybraných algoritmov, ktoré boli primárne vyvinuté pre CPU procesory, avšak vzhľadom k vysokému dopytu po ich vylepšeniach sme sa rozhodli ich využiť v prospech GPGPU (procesorov grafického adaptéra). Modifikácia týchto algoritmov bola zároveň cieľom nášho výskumu, ktorý bol prevedený pomocou CUDA rozhrania. Práca je členená podľa troch skupín algoritmov, ktorým sme sa venovali: detekcia objektov v reálnom čase, spektrálna analýza obrazu a detekcia čiar v reálnom čase. Pre výskum detekcie objektov v reálnom čase sme zvolili použitie LRD a LRP funkcií. Výskum spektrálnej analýzy obrazu bol prevedný pomocou PCA a NTF algoritmov. Pre potreby skúmania detekcie čiar v reálnom čase sme používali dva rôzne spôsoby modifikovanej akumulačnej schémy Houghovej transformácie. Pred samotnou časťou práce venujúcej sa konkrétnym algoritmom a predmetu skúmania, je v úvodných kapitolách, hneď po kapitole ozrejmujúcej dôvody skúmania vybranej problematiky, stručný prehľad architektúry GPU a GPGPU. Záverečné kapitoly sú zamerané na konkretizovanie vlastného prínosu autora, jeho zameranie, dosiahnuté výsledky a zvolený prístup k ich dosiahnutiu. Súčasťou výsledkov je niekoľko vyvinutých produktov.
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GPU Image Processing Library
Čermák, Michal ; Španěl, Michal (referee) ; Smrž, Pavel (advisor)
This work is concerned with architecture of recent Nvidia graphics cards and application programming interface CUDA. That is used to create accelerated image processing library. It place emphasis on testing performance gain compassion with high optimized and used OpenCv library.
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Password Cracking Using PRINCE Algorithm and Fitcrack System
Bolvanský, Dávid ; Ryšavý, Ondřej (referee) ; Hranický, Radek (advisor)
The PRINCE algorithm is a faster and more advanced version of a combination attack. Non-distributed password breaking often encounters its limits, and its applicability to real tasks decreases due to the increasing demand for computing resources of the device. The aim of this work is to design a distributed version of the the PRINCE attack as an extension of Fitcrack system, which focuses on distributed password cracking. The proposed design is implemented and integrated into the Fitcrack system. The work examines the PRINCE attack on a set of experiments, which examines the impact of various configuration options. Part of the experimental part is a comparison of the PRINCE attack with the dictionary and combination attack. The purpose of the comparison is to find cases where the PRINCE attack is better than other attacks. Finally, the integrated PRINCE attack solution in the Fitcrack system is compared with the solution implemented in the Hashtopolis system.
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QR code detection under ROS implemented on the GPU
Hurban, Milan ; Věchet, Stanislav (referee) ; Krejsa, Jiří (advisor)
Tato diplomová práce se zabývá vývojem a implementací algoritmu pro detekci QR kódů s integrací do platformy ROS a výpočty běžícími na grafické kartě. Z rešerše současně dostupných nástrojů a technik je vybrán vhodný postup a algoritmus je napsán jako modul v programovacím jazyce Python, který je snadno integrovatelný do ROS. Ke zprostředkování výpočtů na vícejádrovém hardware, jako jsou grafické karty či vícejádrové procesory, je využita knihovna OpenCL.
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Water Simulation Using GPU
Hanzlíček, Jiří ; Jaroš, Jiří (referee) ; Vaverka, Filip (advisor)
The goal of this thesis is to find a suitable model of fluids, the numerical simulation of which can be realized as interactive program. This requirement leads to a solution based on highly parallel algorithm. The implementation is built not only for CPU, but also GPU in a way, that allows to compare computational performance of each device on selected model.
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MRI Data Processing Acceleration on GPU
Kešner, Filip ; Nečas, Ondřej (referee) ; Polok, Lukáš (advisor)
This BSc Thesis was performed during a study stay at the Universita della Svizzera italiana, Swiss. The identification of trajectories of neuron fibres within the human brain is of great importance in many medical applications as the neural diagnostics, neuronavigation, treatment of epilepsy, surgical removal of tumors and etc. By using diffusion MRI-data as input, and by employing Monte-Carlo like methods, possible trajectories are generated and the most likely ones can be visualized. These can serve as input for advanced medical diagnosis and treatments. Due to the huge amount of data to be analyzed and many iterations, this is a time consuming process. For the purposes such as statistical analysis and comparsion over several datasets or several patients, computational time requirements are enourmous. Faster diagnosis can improve routine throughput and provide earlier treatment of illness. At this time, there exists only a very few implementations of neural tractography sof tware. For probabilistic neural tractography is the list of software even thiner. Today's implementations using standard serial CPU execution suffer from high time consumption. The goal is to provide an efficient implementation which makes use of GPGPUs and exploits parallelism in the method. For the GPU implementation, a comparsion of CUDA and OpenCL technologies will be provided, using the more suitable one.
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General Purpose GPU
Potěšil, Josef ; Černocký, Jan (referee) ; Smrž, Pavel (advisor)
This bachelor's thesis deals with the general-purpose computing on graphics processing units. The examined kind of algorithms are the sorting algorithms. The beginning of this thesis deals with the general-purpose thematic itself, available tools and technologies. It continues with the basic theoretical informations about sorting. At the end the implementation of some sorting algorithms in CUDA, performance tests and the evaulation of these tests are described.
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GPU Raytracer for OSG
Kantor, Jiří ; Horváth, Zsolt (referee) ; Starka, Tomáš (advisor)
This work describes creation of a simple raytracer for OpenSceneGraph, which performs its operations on the graphics card. Things, that needed to be done in OpenSceneGraph in order to pass data to the GPU and also several ray-triangle intersection methods, are described in this work.
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