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Extending Java Performance Monitoring Framework with Support for Windows Performance Counters
Dráb, Martin ; Bulej, Lubomír (advisor) ; Kruliš, Martin (referee)
Java Performance Measurement Framework (JPMF) is a library that allows to collect performance data from underlying operating system. The main goal of the framework is to provide a way of performance data measurement regardless of the application under test. This goal sets the framework apart from many ad-hoc performance measurement solutions targeted at specific applications or middleware platforms. Such solutions collect certain performance data at fixed points of the execution of the application under test. The main goal of this thesis is to implement a library that allows to collect performance statistics of various kinds on machines running Microsoft Windows operating system. The library should be integrated into the framework, which extends its portability.
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Arithmetic coding on GPU
Buneev, Leonid ; Horáček, Jan (advisor) ; Kruliš, Martin (referee)
The aim of this thesis is to investigate possibilities for creating parallel arithmetic coding implementation and measure performance improvements. In the first part, short overview of Arithmetic coding with its serial implementation (FastAC by Amir Said) is presented. The thesis then describes principles of work with GPUs and identifies possibilities of algorithm improvement and parallelization. Several parallel implementations are given, with varying performance improvements and occasional drawbacks. In conclusion, thesis provides results of performance tests of our implementation, as well as discussion about feasibility of applying GPU-oriented version of algorithm instead of serial one in real-world applications. Powered by TCPDF (www.tcpdf.org)
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Cooperative game editor
Žofák, Norbert ; Keznikl, Jaroslav (advisor) ; Kruliš, Martin (referee)
The aim of the work is implementation of a cooperative game editor. The editor is mainly designed for non-programmers, who wish to create their own RPG games, alone or in cooperation with others. Game elements - basic units of the game world - are templated, so users can easily add new game elements to the game world. The game is driven by events, which can be handled by user-defined Lua scripts. User interface of the editor is simple and straightforward with well-arranged lists of game elements and a property editor for easy editing. The editor provides two modes - edit mode and play mode. The latter is designed for immediate testing of currently edited game. Cooperativity of the editor is ensured by synchronization with a database server. The result of a work in the editor is a final game in the form of an executable package.
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Animated visualizations for IVIS framework
Burian, David ; Bureš, Tomáš (advisor) ; Kruliš, Martin (referee)
With the growing volumes of collected data, their presentation and understanding have become much more critical. Visualization frameworks, such as IVIS, continuously develop new ways of graphically presenting data in order to, among other things, improve user experience and data insight. In this thesis, we develop an animation extension for IVIS, which creates a new, interactive and engaging way of exploring data. The resulting animation can play back either time- series or real-time data visualizing their evolution over a period of time. The animation extension relies on already existing IVIS's visualization components. We also focus on developing a new interface allowing the users to control the animation. As part of this thesis, we have designed sample dashboards showcasing the possibilities of the implemented solution. 1
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Remixing OSM maps using recurrent neural networks
Sedlák, Filip ; Kratochvíl, Miroslav (advisor) ; Kruliš, Martin (referee)
Generation of random realistic maps is a highly desirable content creation method for entertainment industry. Neural networks provide powerful com- putational capabilities proven useful in many fields. This thesis describes an algorithm that adapts real-world data to train Recurrent Neural Networks (RNNs) inspired by the pixel RNNs. An algorithm is constructed to gener- ate a map of altitudes, roads, rivers and buildings. The results are tested and evaluated on multiple selected real-world regions. It shows the ability of RNNs to learn and create random realistic maps. Algorithm generates real- istic altitude maps reflecting user input and training dataset. The creation of roads and rivers was met with weaker results. The creation of buildings was met with unsatisfactory results. 1
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Remixing OSM maps using recurrent neural networks
Sedlák, Filip ; Kratochvíl, Miroslav (advisor) ; Kruliš, Martin (referee)
Generation of random realistic maps is a highly desirable content creation method for entertainment industry. Neural networks provide powerful com- putational capabilities proven useful in many fields. This thesis describes an algorithm that adapts real-world data to train Recurrent Neural Networks (RNNs) inspired by the pixel RNNs. An algorithm is constructed to gener- ate a map of altitudes, roads, rivers and buildings. The results are tested and evaluated on multiple selected real-world regions. It shows the ability of RNNs to learn and create random realistic maps. Algorithm generates real- istic altitude maps reflecting user input and training dataset. The creation of roads and rivers was met with weaker results. The creation of buildings was met with unsatisfactory results. 1
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Algorithms for Parallel Searching in XML Datasets
Kruliš, Martin
This thesis will address the problems of indexing XML datasets and finding effective searching methods for indexed data. Defining data structures and algorithms that take highly parallel approach to the searching problem is considered to be main objective, therefore the implementation may benefit from the power of multicore CPUs. Prototype of such implementation will be presented with the thesis. Internal query model will be developed as a common layer. Multiple front-ends representing different query languages will be able to operate on the top of this model, thus the engine will not be dependent on any particular language. Sample front-end for a subset of XPath will be implemented along with the prototype.
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Employing GPU to Process Data from Electron Microscope
Bali, Michal ; Kruliš, Martin (advisor) ; Šikudová, Elena (referee)
Electron backscatter diffraction (EBSD) is a common tool used by phy- sicists to examine crystalline materials, which is based on taking pictures of material microstructure using electron microscope. To determine additional characteristics of studied specimen, a specific variant called High resolution EBSD has been proposed (and partially adopted). The technique takes se- veral subregions of the images taken by the EBSD camera and uses cross- correlation to measure deformation of obtained patterns. Usability of this method is limited by its relatively high computational complexity, which makes it useless for the analysis of larger specimen surfaces. At the same time, processing of individual subregions and images is independent, which makes it appropriate for parallelization provided by modern GPUs. In this thesis, we describe the technique used to process the EBSD data in detail, analyze it and implement the most computationally demanding parts using the CUDA technology. Compared to a reference Python implementation, we measured a speedup of 30-40-times when using a double floating precision and up to a 270-times speedup for a single precision.
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Remotely controlled multi-platform music player
Jurčo, Michal ; Kruliš, Martin (advisor) ; Kopecký, Michal (referee)
Music plays on many places as a primary or secondary tool to make people feel relaxed and in good mood. Most currently available applications focus on what is being played but do not adapt music choice based on who is currently listening to. The most precise way is to let the listeners decide which is what jukeboxes do but they have not caught up with the progress of technology yet. The goal of this thesis was to design and implement a music player where playback can be remotely controlled by multiple users. Application operator may create a music library from songs stored in local files (such as MP3) and organize these songs in playlists. Regular users may explore playlists and enqueue songs into playback. The application is ready for integration with mobile technologies, so regular users may control the playback via a mobile application. 1
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Module for real-time object detection in video stream
Antošík, Vojtěch ; Skopal, Tomáš (advisor) ; Kruliš, Martin (referee)
Over the last few years surveillance cameras have become ubiquitous. With so many cameras, analyzing the output manually has become very laborious and inefficient. In recent years, however, a lot of development has been focused on automatic video process- ing using artificial intelligence. There are many deep learning models for object detection offering basic low-level analysis. This thesis builds upon these models and creates an efficient video processing pipeline that serves as a base for further higher-level analyses. We aim to develop sufficiently fast video processing pipeline that will be able to process surveillance camera video streams in real-time while maintaining low CPU utilization. We move as much of the pipeline as possible to the GPU, with the data never leaving the GPU memory before the very end of the pipeline, and therefore leaving most of the CPU computational power for further data analysis. Our testing shows that our implemen- tation achieves performance very close to real-time with 1080p video even on common consumer hardware. 1
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