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Fluid Simulation
Štambachr, Jakub ; Polok, Lukáš (referee) ; Jošth, Radovan (advisor)
This diploma thesis addresses the problem of liquid and gas simulation, it particularly deals with computer simulation of flow of viscous newtonian liquids with a free surface. A main goal of this work is to create an efficient simulation model, utilizing the benefits of current GPU parallel architecture for general-purpose computing. I chose to implement Smoothed Particle Hydrodynamics, a lagrangian particle-based method. A significant portion of this thesis consists of speed analysis of the implemented algorithm, comparison with other authors' achievements in the field and a demonstration of benefits brought by GPU involvement in the computation. As an output of the thesis I present an interactive computer program that allows for real-time simulation (and visualization) of water-like fluids.
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4K real-time video encoding using NVENC technology
Buchta, Martin ; Přinosil, Jiří (referee) ; Kříž, Petr (advisor)
Diploma thesis is focused on real-time 4K video encoding using NVENC technology. First chapter describes the most used video codecs H.264 and HEVC. There is an explanation of the principle of graphic cards and their programmable units. Analysis of the solution of open source Video Codec SDK is also part of the thesis. The main focus of the thesis is an implementation of an application which can handle 4K video encoding from multiple cameras in real time. Performance and qualitative tests were performed for application. Results of these tests were analyzed and discussed.
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The Use of GPU to Searching for the Secured Wireless Network Keys
Tyrala, Radek ; Pospíchal, Petr (referee) ; Jaroš, Jiří (advisor)
This bachelor thesis proposes an analysis of wireless networks security with a particular focus on Wi-Fi type networks. In order to define the central elements of the thesis, let us follow a description of the main steps, namely: The characteristics of the currently applied security standards are provided together with a discussion of their weak points. A somewhat closer insight is offered into the WPA2 security standard as well as into the related breaking possibilities. A description is realized of the principle of dictionary attacks and their acceleration using parallel processing on the GPU. Another important point presented consists in a comparison of the GPU and CPU performance for an application implementing dictionary attack on wireless networks protected with the 802.11i standard.
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Heat Diffusion Simulation on GPU
Hradecký, Michal ; Vašíček, Zdeněk (referee) ; Jaroš, Jiří (advisor)
This thesis deals with the simulation of heat diffusion in human tissues. The proposed algorithm uses a finite-difference time-domain method, which is applied on the governing equation describing the system. A modern graphics card is used to accelerate the simulation. The performance achieved on the GPU card is compared with the implementation exploiting a modern multicore CPU. The output of this thesis is a set of differently optimized algorithms targeted on NVIDIA graphics cards. The experimental results reveal that the use of shared memory is contraproductive and the best performance is achieved by a register based implementation. The overall speedup of 18.5 was reached when comparing a NVIDIA GeForce GTX 580 with a quad-core Intel Core i7 920 CPU. This nicely corresponds with the theoretical capabilities of both architectures.
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Simulation of Ultrasound Propagation in Bones
Kadlubiak, Kristián ; Vaverka, Filip (referee) ; Jaroš, Jiří (advisor)
It is estimated that mind-boggling 14.1 million new cases of cancer occurred worldwide in 2012 alone. This number is alarming. Although healthy lifestyle may reduce a risk of developing cancer, there is always some probability that cancer would develop even in an absolutely fit individual. There are two main conditions for successful treatment of cancer. Firstly, early diagnostic is absolutely crucial. Secondly, there is a need for suitable surgical methods for affected tissue removal. Ultrasound has a great potential to be used for both purposes as a non-invasive method. Photoacoustic spectroscopy is imaging method for tumor detection of great properties making the use of ultrasound while High-Intensity Focused Ultrasound (HIFU) is non-invasive surgical method. These methods would be impossible without precise ultrasound propagation simulations. The k-Wave is an open source MATLAB toolbox implementing such simulations. So, why are not these methods already deployed in treatment? Unfortunately, the simulation of ultrasound propagation is a very time consuming task, which makes it ineffective for medical purposes. However, there are a few options how to accelerate these simulations. The use of GPU is a very promising way to accelerate simulation. The main topic of this thesis is the acceleration of the simulation of soundwaves propagation in bones and hard tissue. The implementation developed as a part of this thesis was benchmarked on various supercomputers including Anselm in Ostrava and Piz Daint in Lugano. The implemented solution provides remarkable acceleration compared to the original MATLAB prototype. It was able to accelerate the simulation around 160 times in the best case. It means that the simulation, which would otherwise last for 6.5 days, can be now computed in one hour. This acceleration was achieved using an NVIDIA Tesla P100 to run the simulation with the domain size of 416x416x416 grid points. The thesis includes performance benchmarks on different GPUs to provide complex image acceleration capabilities of developed implementation and provides discussion about memory usage and numerical accuracy. Thanks to the implemented solution harnessing the power of modern GPUs, doctors and researchers all around the world have a powerful tool in hands.
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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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GPGPU parallel computing
Pacura, Dávid ; Horák, Karel (referee) ; Petyovský, Petr (advisor)
The aim of this trim’s thesis is to reveal possibilities and demonstrate parallelization of computation on graphics processors. The paper presents descriptions of available development tools, and then one of them is selected to implement MD5 encryption algorithm and neural network for optical character recognition. Its performance is then compared to its parallel equivalent for conventional processors. In conclusion, problems encountered during development are described, and ways of avoiding them are discussed.
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