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Ray Tracing on CUDA Architecture
Bidmon, Lukáš ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This work presents utilization of CUDA capable graphic cards for ray tracing. First, the classic recursive ray tracing algorithm is presented and necessary math is explained for implemented objects. nVidia CUDA architecture is introduced in next chapter with explained differences from CPU computations. Following is the implementation scheme where modifications necessary for CUDA are discussed. Implementation chapter covers details about flow of the program and memory usage. Finally the CPU and GPU testing results are presented.
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Computations in Physics Using Graphic Card Procesor
Hlůšek, Bronislav ; Poliščuk, Radek (referee) ; Ondroušek, Vít (advisor)
This work deals with issue of general purpose computation on graphics processing units. It provides basic information about the graphics hardware. It also describes CUDA and CTM programming interface, that are intended specially for these calculations and features and alternative methods solving. There are as well mentioned possibilities their usage and several practical instances calculations.
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GPGPU Libraries Benchmark
Kula, Michal ; Korček, Pavol (referee) ; Pospíchal, Petr (advisor)
Bachelor´s thesis deals with principles of graphics adaptors work and their using for common calculations by the help of graphics library and bachelor´s thesis deals also with comparing of these libraries. In the bachelor´s thesis, there is explanation of suitability of graphics adaptors usage for different types of calculations, restrictions and efficiency usage of programming method on basis of principles of graphics adaptors work. In the bachelor´s thesis, there are comparisons of graphics libraries Nvidia Cuda and OpenCL, their comparisons both in transfer rates and for simple and complex calculations. Bachelor´s thesis results are interpretations of tests and suitability assessments of utilization of graphics libraries in selected calculations.
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A dynamical particle system as a driver for optimal statistical sampling
Mašek, Jan ; Šejnoha,, Jiří (referee) ; Kruis,, Jaroslav (referee) ; Vořechovský, Miroslav (advisor)
The presented doctoral thesis aims at development a new efficient tool for optimization of uniformity of point samples. One of use-cases of these point sets is the usage as optimized sets of integration points in statistical analyses of computer models using Monte Carlo type integration. It is well known that the pursuit of uniformly distributed sets of integration points is the only possible way of decreasing the error of estimation of an integral over an unknown function. The tasks of the work concern a survey of currently used criteria for evaluation and/or optimization of uniformity of point sets. A critical evaluation of their properties is presented, leading to suggestions towards improvements in spatial and statistical uniformity of resulting samples. A refined variant of the general formulation of the phi optimization criterion has been derived by incorporating the periodically repeated design domain along with a scale-independent behavior of the criterion. Based on a notion of a physical analogy between a set of sampling points and a dynamical system of mutually repelling particles, a hyper-dimensional N-body system has been selected to be the driver of the developed optimization tool. Because the simulation of such a dynamical system is known to be a computationally intensive task, an efficient solution using the massively parallel GPGPU platform Nvidia CUDA has been developed. An intensive study of properties of this complex architecture turned out as necessary to fully exploit the possible solution speedup.
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Acceleration of Data Compression Algorithms Using GPU
Cacek, Pavel ; Drábek, Vladimír (referee) ; Šimek, Václav (advisor)
This bachelor's thesis is dealing with possibility of acceleration compression algorithm on graphical card. I have studied specifically the compression algorithm JPEG, which is used for compression image data. The text first introduced technology, which give access to us use computational power of graphics cards. The work is also focused on the theoretical description of the JPEG and subsequently is describe its implementation using OpenCL and NVIDIA CUDA. Finally, there is a comparison of performance this GPGPU technologies.
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The GPU-Based Acceleration of the Genetic Algorithm
Pospíchal, Petr ; Šimek, Václav (referee) ; Jaroš, Jiří (advisor)
This thesis represents master's thesis focused on acceleration of Genetic algorithms using GPU. First chapter deeply analyses Genetic algorithms and corresponding topics like population, chromosome, crossover, mutation and selection. Next part of the thesis shows GPU abilities for unified computing using both DirectX/OpenGL with Cg and specialized GPGPU libraries like CUDA. The fourth chapter focuses on design of GPU implementation using CUDA, coarse-grained and fine-grained GAs are discussed, and completed by sorting and random number generation task accelerated by GPU. Next chapter covers implementation details -- migration, crossover and selection schemes mapped on CUDA software model. All GA elements and quality of GPU results are described in the last chapter.
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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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GPU Acceleration of Graph Algorithms
Lorenc, David ; Andriushchenko, Roman (referee) ; Češka, Milan (advisor)
In this bachelor thesis, I will deal with the acceleration of the Breadth-first search (BFS) algorithm on a graphics card. This is an algorithm designed to traverse the graph in breadth. I will explain the basic parallelization techniques divided according to Flynn’s classification. I will also discuss the existing methods of parallelizing BFS on GPU. I will then perform structured experiments of all approaches on the same dataset, compare and evaluate the results. It is very difficult for someone new to the field to navigate through it, due to its vastness, I wanted to create a work that will guide a programmer new to parallelization on GPUs and give them an easier insight into the subject. Furthermore, I focused on structured testing of different approaches from different works and evaluated them for the sake of reviewing the performance of the approaches in one place. Thus, the reader can see which one is most suitable for his/her need. A clear explanation of the theory behind parallelization techniques and problems, and a description of the hardware and software concepts of NVDIA Cuda. An introduction to the possibilities of representing graphs in memory and an explanation of why graph representation using a neighborhood list is used. Description of the different approaches and their testing, based on the results of the evaluation of the effectiveness of the approaches.
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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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A dynamical particle system as a driver for optimal statistical sampling
Mašek, Jan ; Šejnoha,, Jiří (referee) ; Kruis,, Jaroslav (referee) ; Vořechovský, Miroslav (advisor)
The presented doctoral thesis aims at development a new efficient tool for optimization of uniformity of point samples. One of use-cases of these point sets is the usage as optimized sets of integration points in statistical analyses of computer models using Monte Carlo type integration. It is well known that the pursuit of uniformly distributed sets of integration points is the only possible way of decreasing the error of estimation of an integral over an unknown function. The tasks of the work concern a survey of currently used criteria for evaluation and/or optimization of uniformity of point sets. A critical evaluation of their properties is presented, leading to suggestions towards improvements in spatial and statistical uniformity of resulting samples. A refined variant of the general formulation of the phi optimization criterion has been derived by incorporating the periodically repeated design domain along with a scale-independent behavior of the criterion. Based on a notion of a physical analogy between a set of sampling points and a dynamical system of mutually repelling particles, a hyper-dimensional N-body system has been selected to be the driver of the developed optimization tool. Because the simulation of such a dynamical system is known to be a computationally intensive task, an efficient solution using the massively parallel GPGPU platform Nvidia CUDA has been developed. An intensive study of properties of this complex architecture turned out as necessary to fully exploit the possible solution speedup.
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