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The algorithms of digital image processing on graphics cards
Bielczyk, Marek ; Lattenberg, Ivo (referee) ; Přinosil, Jiří (advisor)
Purpose of this work is show possibility of using grapichs cart for imaging a video signal. This work is particularly focused on technology CUDA and OpenCL. The solution is first focused on graphics cart and show how has been changed components and how has been changed performaces of graphics cart. Then show CUDA and OpenCL technology itself, and show samples of codes with explain, what which code do. Output of this work is some programs, witch defined for both technology and for both procesors unit. Contribution of this work is show differents between procesors unit, witch can be used to right choose for design your own algorithm.
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Algorithm Acceleration on Larrabee Platform
Veselý, Ivo ; Seeman, Michal (referee) ; Zemčík, Pavel (advisor)
Intel Larrabee is one of the first of fully programmable graphical architectures. Thesis describes this many-core architecture by hardware implementation and programmer's model point of view. Larrabee bets on many complete in-order cores, built over x86 instruction set. Cores contains four hardware threads, each with it's own register file, and new vector processing unit. Vector processing unit together with instruction set extension rapidly increases system performance. New cache modes helps to increase throughput even when irregular data structures. This architecture is not focused only on computer graphics nor image processing, but all parallel tasks. Second part of this text deals with hologram synthesis. Specifically, it brings two new methods for patch of point light sources generation with concrete radiation.
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The exploitation of parallelization to numerical solutions regarding problems in nonlinear dynamics
Rek, Václav ; Krejsa,, Martin (referee) ; Vala, Jiří (referee) ; Němec, Ivan (advisor)
The main aim of this thesis is the exploration of the potential use of the parallelism of numerical computations in the field of nonlinear dynamics. In the last decade the dramatic onset of multicore and multi-processor systems in combination with the possibilities which now provide modern computer networks has risen. The complexity and size of the investigated models are constantly increasing due to the high computational complexity of computational tasks in dynamics and statics of structures, mainly because of the nonlinear character of the solved models. Any possibility to speed up such calculation procedures is more than desirable. This is a relatively new branch of science, therefore specific algorithms and parallel implementation are still in the stage of research and development which is attributed to the latest advances in computer hardware, which is growing rapidly. More questions are raised on how best to utilize the available computing power. The proposed parallel model is based on the explicit form of the finite element method, which naturaly provides the possibility of efficient parallelization. The possibilities of multicore processors, as well as parallel hybrid model combining both the possibilities of multicore processors, and the form of the parallelism on a computer network are investigated. The designed approaches are then examined in addressing of the numerical analysis regarding contact/impact phenomena of shell structures.
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Parallel implementation of Goertzel algorithm
Skulínek, Zdeněk ; Smékal, Zdeněk (referee) ; Sysel, Petr (advisor)
Technical problems make impossible steadily increase processor's clock frequency. Their power are currently growing due to increasing number of cores. It brings need for new approaches in programming such parallel systems. This thesis shows how to use paralelism in digital signal processing. As an example, it will be presented here implementation of the Geortzel's algorithm using the processing power of the graphics chip.
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Signal processing using parallel mathematical operations
Polášek, Jaromír ; Ležák, Petr (referee) ; Mžourek, Zdeněk (advisor)
This Bachelor thesis deals with the acceleration of function calculations, using parallel computing mediated by NVDIA graphics cards via CUDA technology. The theoretical part describes the general principles of parallel computing and the basic characteristics and parameters of graphics cards NVDIA. The theoretical part also deals with basic principles of CUDA technology. End of the theoretical part focuses on FFTW and cuFFT libraries. The practical part deals with the comparison of the performance between GPU and CPU functions filter2D and Canny and practical possibilities of accelerating fast convolution calculation. The practical part also describes sample code that was used to compare the performance between GPU and CPU. The results of this program are then plotted and evaluated.
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Deformation mechanisms in crystals by means of molecular dynamics
Lamberský, Vojtěch ; Grepl, Robert (referee) ; Černý, Miroslav (advisor)
This work deals with molecular dynamics modeling of processes in condensed matter on atomic level. The physical principles used to predict motion of atom or molecule groups are described in the retrieval part. Then follows a description of the EAM method, ways how to parallelize computing on many processors and how perform calculation optimizing. Finally, we perform a theoretical tensile strength computation using Lammps program.
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Parallel Deep Learning
Šlampa, Ondřej ; Sochor, Jakub (referee) ; Hradiš, Michal (advisor)
Aim of this thesis is to propose how to evaluate favourableness of parallel deep learning. In this thesis I analyze parallel deep learning and I focus on its length. I take into account gradient computation length and weight transportation length. Result of this thesis is proposal of equations, which can estimate the speedup on multiple workers. These equations can be used to determine ideal number of workers for training.
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Parallelization of complex tasks in reconstruction of dynamic magnetic resonance
Bijotová, Kateřina ; Rajmic, Pavel (referee) ; Mašek, Jan (advisor)
This thesis deals with parallelization of complex tasks in reconstruction of dynamic magnetic resonance. It describes the basic principle of magnetic resonance and its relation to Fourier transform. It deals with the difference between static and dynamic magnetic resonance image reconstruction. It analyzes SVD algorithm and its use in magnetic resonance image reconstruction. It presents the principles and the importance of parallel computing in magnetic resonance imaging and describes CUDA technology. The thesis also contains a description and execution of the implementation of the reconstruction model in MATLAB and Java programming language which were optimized by JCuda library for Java implementation and gpuArray function in case of MATLAB implementation.
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GPU-Accelerated Design of Optically Generated Ultrasound Using Binary Amplitude Holograms
Knotek, Martin ; Vaverka, Filip (referee) ; Jaroš, Jiří (advisor)
In this thesis, we deal with the possibilities of the acceleration of scientific computations using the graphical processing unit. The term scientific computation in this context means an algorithm, which computes binary holograms that are used to generate ultrasound. We will concentrate specifically on the design of the hologram, focusing at the speed we can achieve when computing the surface of the hologram. For this purpose, we will use two popular parallel data processing platforms - CUDA and OpenMP. The surface design pattern of the hologram is important due to the fact, that it determines the hologram’s specific physical characteristics.
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Parallelization of complex tasks in reconstruction of dynamic magnetic resonance
Bijotová, Kateřina ; Rajmic, Pavel (referee) ; Mašek, Jan (advisor)
This thesis deals with parallelization of complex tasks in reconstruction of dynamic magnetic resonance. It describes the basic principle of magnetic resonance and its relation to Fourier transform. It deals with the difference between static and dynamic magnetic resonance image reconstruction. It analyzes SVD algorithm and its use in magnetic resonance image reconstruction. It presents the principles and the importance of parallel computing in magnetic resonance imaging and describes CUDA technology. The thesis also contains a description and execution of the implementation of the reconstruction model in MATLAB and Java programming language which were optimized by JCuda library for Java implementation and gpuArray function in case of MATLAB implementation.
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