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Password Cracking with Rainbow Tables on GPU
Jahoda, David ; Holop, Patrik (referee) ; Malinka, Kamil (advisor)
This thesis focuses on the design and implementation of a password cracking tool using Rainbow tables with GPU acceleration. Emphasis is placed on the tool's performance, utilizing contemporary software and hardware resources. In the experimental section, a comparison is made with existing solutions employing Rainbow tables and counter measures against them.
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Augmented Reality in Industrial Production and Maintenance
Kajan, Matej ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper seeks to explore the possibility to utilize XR (extended reality) in industrial assembly. The aim is to implement a system, which is able to visually navigate the operator during the product assembly process by the means of object recognition and image augmentation. The first chapter presents the use-case of augmented reality in the industry. The next part consists of research on the topic of augmented and virtual reality devices and provides a brief comparison of the current state of the art. Afterwards, a methodology is presented for object recognition of an arbitrary object. The implementation is able to detect the object in real-time, is resilient to occlusion and contains the information about the object’s orientation.
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Acceleration of Ultrasound Neurostimulation Using Multi-GPU Systems
Bayer, David ; Kadlubiak, Kristián (referee) ; Jaroš, Jiří (advisor)
This theses is focused on extending the accelerated implementation of propagating acoustic waves in a medium simulation of k-Wave toolbox by the possibility of using multiple GPUs for the computation. It first describes multi-GPU systems in general and the tools that can be used to work with them. It continues with a description of the k-Wave toolbox and an analysis of existing accelerated implementations. Selected technologies are then tested on a heat diffusion in a medium simulation and the results are used to select tools for the design a resulting implementation. Finally, it summarizes the results obtained.
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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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Interactive Cloth Simulation Accelerated by GPU
Melichar, Vojtěch ; Klepárník, Petr (referee) ; Jaroš, Jiří (advisor)
This master thesis deals with interactive cloth simulation accelerated by GPU. In the first part there is a description of all technologies used during implementation of a program. The second part discusses various simulation methods. It is mainly focused on particle systems as a most used method. These parts are followed by a design of the program, which is implemented as a part of this thesis. The program was implemented in four variants. The first variant is CPU implementation, which was then optimalized with OpenMP. CUDA implementation is based on these implementations. Last variant implemented in this thesis is optimized CUDA implementation. All these implementations are evaluated from compute complexity point of view and suitability for real time graphics.
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The Parallel Genetic Algorithm for Multicore Systems
Vrábel, Lukáš ; Šimek, Václav (referee) ; Jaroš, Jiří (advisor)
Genetický algoritmus je optimalizačná metóda zameraná na efektívne hľadanie riešení rozličných problémov. Je založená na princípe evolúcie a prirodzeného výberu najschopnejších jedincov v prírode. Keďže je táto metóda výpočtovo náročná, bolo vymyslených veľa spôsobov na jej paralelizáciu. Avšak väčšina týchto metód je z historických dôvodov založená na superpočítačoch alebo rozsiahlych počítačových systémoch. Moderný vývoj v oblasti informačných technológií prináša na trh osobných počítačov stále lacnejšie a výkonnejšie viacjadrové systémy. Táto práca sa zaoberá návrhom nových metód paralelizácie genetického algoritmu, ktoré sa snažia naplno využiť možnosti práve týchto počítačových systémov. Tieto metódy sú následne naimplementované v programovacom jazyku C za využitia knižnice OpenMP určenej na paralelizáciu. Implementácia je následne použitá na experimentálne ohodnotenie rozličných charakteristík každej z prezentovaných metód (zrýchlenie oproti sekvenčnej verzii, závislosť konvergencie výsledných hodnôt od miery paralelizácie alebo od vyťaženia procesoru, ...). V poslednej časti práce sú prezentované porovnania nameraných hodnôt a závery vyplývajúce z týchto meraní. Následne sú prediskutované možné vylepšenia daných metód vyplývajúce z týchto záverov, ako aj možnosti spracovania väčšieho množstva charakteristík na presnejšie ohodnotenie efektivity paralelizácie genetických algoritmov.
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Acceleration of Lattice-Boltzmann Algorithms for Bloodflow Modeling
Kompová, Radmila ; Kešner, Filip (referee) ; Jaroš, Jiří (advisor)
This thesis aims to explore possible implementations and optimizations of the lattice-Boltzmann method. This method allows modeling of fluid flow using a simulation of fictive particles. The thesis focuses on possible improvements of the existing tool HemeLB which is designed and optimized for bloodflow modeling. Several vectorization and paralellization approaches that could be included in this tool are explored. An application focused on comparing chosen algorithms including optimizations for the lattice-Boltzmann method was implemented as a part of the thesis. A group of tests focused on comparing this algorithms according to performance, cache usage and overall memory usage was performed. The best performance achieved was 150 millions of lattice site updates per second.
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Simulation of Heat Diffusion in the Brain Using High-Level GPGPU Techniques
Krbila, Martin ; Kadlubiak, Kristián (referee) ; Jaroš, Jiří (advisor)
This master's thesis deals with acceleration of heat diffusion simulation using graphics cards. It describes an approach to acceleration of an existing implementation in Matlab, which is a part of k-Wave package. Various high-level as well as low-level libraries for GPU programming are introduced here and their strengths and weaknesses compared. A complete implementation of the simulation on GPU was created as a part of this work. This implementation achieves around hundredfold speedup over the existing CPU solution in Matlab. A module for computation of discrete trigonometric transformations on graphics card was created to accelerate simulation with various boundary conditions. This module achieves around ten times speedup over the best CPU implementation. Another output of this thesis is a performance comparison of several implementations of basic diffusion simulation each using a different GPGPU technique.
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Implementation of 2D Ultrasound Simulations
Šimek, Dominik ; Vaverka, Filip (referee) ; Jaroš, Jiří (advisor)
The work deals with design and implementation of 2D ultrasound simulation. Applications of the ultrasound simulation can be found in medicine, biophysic or image reconstruction. As an example of using the ultrasound simulation we can mention High Intensity Focused Ultrasound that is used for diagnosing and treating cancer. The program is part of the k-Wave toolbox designed for supercomputer systems, specifically for machines with shared memory architecture. The program is implemented in the C++ language and using OpenMP acceleration. Using the designed solution, it is possible to solve large-scale simulations in 2D space. The work also deals with merging and unification of the 2D and 3D simulation using modern C++. A realistic example of use is ultrasound simulation in transcranial neuromodulation and neurostimulation in large domains, which have more than 16384x16384 grid points. Simulation of such size may take several days if we use the original MATLAB 2D k-Wave. Speedup of the new implementation is up to 8 on the Anselm and Salomon supercomputers.
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