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Paralelizace ultrazvukových simulací pomocí 2D dekompozice / Parallelization of Ultrasound Simulations Using 2D DecompositionNikl, Vojtěch January 2014 (has links)
This thesis is a part of the k-Wave project, which is a toolbox for the simulation and reconstruction of acoustic wave felds and one of its main contributions is the planning of focused ultrasound surgeries (HIFU). One simulation can take tens of hours and about 60% of the simulation time is taken by the calculation of the 3D Fast Fourier transforms. Up until now the 3D FFT has been calculated purely by the FFTW library and its 1D decomposition, whose major limitation is the maximum number of employable cores. Therefore we introduce a new approach, called the 2D hybrid decomposition of the 3D FFT (HybridFFT), where we combine both MPI processes and OpenMP threads to reach as best performance as possible. On a low number of cores, on the order of a few hundreds, we are about as fast or slightly faster than FFTW and pure MPI 2D decomposition libraries (PFFT and P3DFFT). One of the best results was achieved on a 512^3FFT using 512 cores, where our hybrid version run 31ms, FFTW run 39ms and PFFT run 44ms. The most significant performance advantage should be seen when employing around 8-16 thousand cores, however we haven't had an access to a machine with such resources. Almost a linear scalability has been proven for up to 2048 employed cores.
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Intel Integrated Performance Primitives a jejich využití při vývoji aplikací / Intel Integrated Performance Primitives and their use in application developmentMachač, Jiří January 2008 (has links)
The aim of the presented work is to demonstrate and evaluate the contribution of computing system SIMD especially units MMX, SSE, SSE2, SSE3, SSSE3 and SSE4 from Intel company, by creation of demostrating applications with using Intel Integrated Performance Primitives library. At first, possibilities of SIMD programming using intrinsic function, vektorization and libraries Intel Integrated Performance Primitives are presented, as next are descibed options of evaluation of particular algorithms. Finally procedure of programing by using Intel Integrated Performance Primitives library are ilustrated.
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Efektivní implementace genetického algoritmu s využitím vícejádrových CPU / The Efficient Implementation of the Genetic Algorithm Using Multicore ProcessorsKouřil, Miroslav January 2010 (has links)
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.
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Akcelerace vektorových a krytografických operací na platformě x86-64 / Acceleration of Vector and Cryptographic Operations on x86-64 PlatformŠlenker, Samuel January 2017 (has links)
The aim of this thesis was to study and subsequently process a comparison of older and newer SIMD processing units of modern microprocessors on the x86-64 platform. The thesis provides an overview of the fastest computations of vector operations with matrices and vectors, including corresponding source codes. Furthermore, the thesis is focused on authenticated encryption, specifically on block cipher AES operating in Galois Counter Mode, and on a discussion of possibilities of instruction sets for cryptographic support.
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An investigation into the relevance of international portfolio diversification from a South African perspectiveBuwembo, Mark January 2020 (has links)
Magister Commercii - MCom / Diversification is one of the more familiar concepts in finance because of its ability
to curtail risk towards investors. However, for diversification to be efficient, the
assets combined should have inversely related price movements. In the same light,
previous research done on international portfolio diversification has consistently
found that having investments diversified across different global markets that have
low to medium correlations helps to get as close to an optimal portfolio as possible.
However, previous research also indicates that both global financial integration and
exogenous shocks increase correlations among international markets, hence
negating the benefits of international portfolio diversification to an extent.
Therefore, with global integration on the rise, coupled with economic and political
instability in some BRICS nations, the research examines these factors and gauges
the current viability of international portfolio diversification from the perspective
of a South African investor.
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Supporting Applications Involving Dynamic Data Structures and Irregular Memory Access on Emerging Parallel PlatformsRen, Bin 09 September 2014 (has links)
No description available.
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Optimalizované sledování paprsku / Optimized Ray TracingBrich, Radek Unknown Date (has links)
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.
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Applications of Artificial Intelligence in Power SystemsRastgoufard, Samin 18 May 2018 (has links)
Artificial intelligence tools, which are fast, robust and adaptive can overcome the drawbacks of traditional solutions for several power systems problems. In this work, applications of AI techniques have been studied for solving two important problems in power systems.
The first problem is static security evaluation (SSE). The objective of SSE is to identify the contingencies in planning and operations of power systems. Numerical conventional solutions are time-consuming, computationally expensive, and are not suitable for online applications. SSE may be considered as a binary-classification, multi-classification or regression problem. In this work, multi-support vector machine is combined with several evolutionary computation algorithms, including particle swarm optimization (PSO), differential evolution, Ant colony optimization for the continuous domain, and harmony search techniques to solve the SSE. Moreover, support vector regression is combined with modified PSO with a proposed modification on the inertia weight in order to solve the SSE.
Also, the correct accuracy of classification, the speed of training, and the final cost of using power equipment heavily depend on the selected input features. In this dissertation, multi-object PSO has been used to solve this problem. Furthermore, a multi-classifier voting scheme is proposed to get the final test output. The classifiers participating in the voting scheme include multi-SVM with different types of kernels and random forests with an adaptive number of trees. In short, the development and performance of different machine learning tools combined with evolutionary computation techniques have been studied to solve the online SSE. The performance of the proposed techniques is tested on several benchmark systems, namely the IEEE 9-bus, 14-bus, 39-bus, 57-bus, 118-bus, and 300-bus power systems.
The second problem is the non-convex, nonlinear, and non-differentiable economic dispatch (ED) problem. The purpose of solving the ED is to improve the cost-effectiveness of power generation. To solve ED with multi-fuel options, prohibited operating zones, valve point effect, and transmission line losses, genetic algorithm (GA) variant-based methods, such as breeder GA, fast navigating GA, twin removal GA, kite GA, and United GA are used. The IEEE systems with 6-units, 10-units, and 15-units are used to study the efficiency of the algorithms.
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Hodnocení informačních systémů / Information System AssesmentMenšík, Marek January 2009 (has links)
This diploma thesis deals with information systems evaluation from user and producer aspects. The theoretical part presents current trends and actual ways of using, including practical application used in real firms. The practical part is focused on proposals and changes for concrete producer of information system.
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Distributed Ray Tracing v rozumném čase / Distributed Ray Tracing in Reasonable TimeSlovák, Radek January 2011 (has links)
This thesis deals with the method of distributed ray tracing focusing on optimalization of this method. The method uses simulation of some attributes of light by distributing rays of lights and it produces high quality and partly realistic images. The price for realitic effects is the high computational complexity of the method. The thesis analysis the theory connected with these aspects. A large part describes optimalizations of this method, i.e. searching for the nearest triangle intersection using kd-trees, quasi random sampling with faster convergence, the use of SSE instruction set and fast ray - triangle intersection. These optimalizations brought a noticable speed - up. The thesis includes description of implementation of these techniques. The implementation itself emphasises the practical usability including generating some advanced animations and universal description of objects.
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