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Geometrical Image Transforms
Němeček, Petr ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This master's thesis deals with acceleration of geometrical image transforms using the GPU and NVIDIA (R) CUDA TM architecture. Time critical parts of the code are moved on the GPU and executed in parallel. One of the results is a demonstrational application for performance comparison of both architectures: the CPU, and GPU in combination with the CPU. As a reference implementation, there are used highly optimized routines from the OpenCV library, made by the Intel company.
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Pixel Interpolation Methods
Mintěl, Tomáš ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This master's thesis deals with acceleration of pixel interpolation methods using the GPU and NVIDIA (R) CUDA TM architecture. Graphic output is represented by a demonstrational application for geometrical image transforms using chosen interpolation method. Time critical parts of the code are moved on the GPU and executed in parallel. There are used highly optimized routines from the OpenCV library, made by the Intel company for an image and video processing.
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Acceleration of Discrete Optimization Heuristics Using GPU
Pecháček, Václav ; Jaroš, Jiří (referee) ; Pospíchal, Petr (advisor)
Thesis deals with discrete optimization problems. It focusses on faster ways to find good solutions by means of heuristics and parallel processing. Based on ant colony optimization (ACO) algorithm coupled with k-optimization local search approach, it aims at massively parallel computing on graphics processors provided by Nvidia CUDA platform. Well-known travelling salesman problem (TSP) is used as a case study. Solution is based on dividing task into subproblems using tour-based partitioning, parallel processing of distinct parts and their consecutive recombination. Provided parallel code can perform computation more than seventeen times faster than the sequential version.
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Particle Swarm Optimization on GPUs
Záň, Drahoslav ; Petrlík, Jiří (referee) ; Jaroš, Jiří (advisor)
This thesis deals with a population based stochastic optimization technique PSO (Particle Swarm Optimization) and its acceleration. This simple, but very effective technique is designed for solving difficult multidimensional problems in a wide range of applications. The aim of this work is to develop a parallel implementation of this algorithm with an emphasis on acceleration of finding a solution. For this purpose, a graphics card (GPU) providing massive performance was chosen. To evaluate the benefits of the proposed implementation, a CPU and GPU implementation were created for solving a problem derived from the known NP-hard Knapsack problem. The GPU application shows 5 times average and almost 10 times the maximum speedup of computation compared to an optimized CPU application, which it is based on.
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GPU Accelerated SAT Solver
Izrael, Petr ; Šimek, Václav (referee) ; Jaroš, Jiří (advisor)
This thesis is concerned with design and implementation of a complete SAT solver accelerated on GPU. The achitecture of modern graphics cards is described as well as the CUDA platform and a list of common algorithms used for solving the boolean satisfiability problem (the SAT problem). The presented solution is based on the 3-SAT DC alogirthm, which belongs to the family of well-known DPLL based algorithms. This work describes problems encountered during the design and implementation. The resulting application was then analyzed and optimized. The presented solver cannot compete with state of the art solvers, but proves that it can be up to 21x faster than an equivalent sequential version. Unfortunately, the current implementation can only handle formulas of a limited size. Suggestions on further improvements are given in final sections.
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GPU Accelerated Ciphers Cracking
Schmied, Jan ; Kajan, Michal (referee) ; Veselý, Vladimír (advisor)
This work describes one - way hash functions and cryptographic algorithms . It also describes their implementation regarding DOC, PDF and ZIP files contents encryption . Subsequently , the implementation analyzis is provided . Following next, the brute - force attack procedure levereging GPU is proposed and evaluated.
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The GPU Accelerated Optimisation of the Water Management Systems
Marek, Jan ; Petrlík, Jiří (referee) ; Jaroš, Jiří (advisor)
Subject of this thesis is optimalization of storage function of water management system. The work is based on dissertation thesis of Ing. Pavel Menšík Ph.D. Automatization of storage function of water management system. As optimalization method was chosen diferential evolution. Sequential version of the method will be implemented as a first step, followed by CPU accelerated and GPU accelerated versions.
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Optical Field Evaluations for Hologram Synthesis
Fedorko, Matúš ; Polok, Lukáš (referee) ; Zemčík, Pavel (advisor)
The primary concern of this work is computer generated holography, in particular accelerating computation of synthetic holograms by means of modern-day massively parallel graphics chips. It starts by introducing fundamental holography principles together with mathematical and physical concepts behind it. Following discussion then deals with OpenCL, which is a relatively new, but well recognized standard for GP-GPU programming. Finally, the last two chapters of this work give an overview of problem analysis and its implementation in C++.
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Medical Data Rendering in Real-Time
Lengyel, Kristián ; Havel, Jiří (referee) ; Jošth, Radovan (advisor)
This thesis deals with design and implementation of an application for medical data imaging in real-time. The first part of project is focused on methods for obtaining data in medical practice and visualization of large volume data on computer using familiar rendering approaches. Similar applications are used outside of medicine in other fields, such as chemistry to display molecular structures or microorganisms. Another part of project will focus on benefits of visualization of volumetric data using programmable hardware and new methods of parallelization of algorithms on graphics card using CUDA technology, and OpenCL. The resulting application will display the volume of medical data based on selected method accelerated by programmable shaders, and time-consuming operations will be paralleled on graphics card.
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Pathtracing on GPU
Březina, Karel ; Kobrtek, Jozef (referee) ; Polok, Lukáš (advisor)
This bachelor thesis focuses on the acceleration of rendering algorithm pathtracing. Thesis's goal is demonstration and performance comparison between implementation on CPU and GPU. Both implementations will be discussed and compared between themselves. Furthermore, will be describe possibilities of extending existing application.
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