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Rasterizace vektorových fontů na LCD
Hrušovský, Marek ; Přibyl, Jaroslav (oponent) ; Granát, Jiří (vedoucí práce)
Táto bakalárska práca sa zaoberá sub-pixelovovým zobrazením vektorového písma. Všeobecne popisuje reprezentáciu a vykreslovanie vektorového písma. Stručne porovnáva výhody oproti reprezentácii bitmapového písma. Zahrňuje informácie o sub-pixelovom zobrazení písma na monitoroch typu LCD, možnostiach a problémoch, ktoré tento typ zobrazenia prináša. Obsahuje popis implementácie demonštračného programu, ktorý vykresluje písmo pomocou sub-pixelov.
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Genetic Algorithm Acceleration Using OpenCL
Hrušovský, Marek ; Šimek, Václav (oponent) ; Jaroš, Jiří (vedoucí práce)
This thesis tries to accelerate genetic algorithm (GA) using OpenCL standard. Acceleration is important for the industry that solves complex problems suitable for GA. The first part of the work contains theoretical background that is needed to understand the topic of parallelization GA and the OpenCL standard. The N-queens problem was chosen to demonstrate the capabilities of accelerating permutation genetic algorithm using the OpenCL standard. The designed model uses for acceleration two GPU cards. The last part of the work deals with benchmarking the parts that are important for GA. One random generator on the GPU is approximately 80 times faster than parallel version on the CPU. One evaluation method can be up to 8000 times faster on the GPU than on the CPU. The crossover functions did not obtain any significant speed-up. However, the parts are capable to obtain speed-ups but due to selection and crossover genetic algorithm operator the whole run of parallel GA on the GPU is maximally twice as fast as on the CPU.
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Rasterizace vektorových fontů na LCD
Hrušovský, Marek ; Přibyl, Jaroslav (oponent) ; Granát, Jiří (vedoucí práce)
Táto bakalárska práca sa zaoberá sub-pixelovovým zobrazením vektorového písma. Všeobecne popisuje reprezentáciu a vykreslovanie vektorového písma. Stručne porovnáva výhody oproti reprezentácii bitmapového písma. Zahrňuje informácie o sub-pixelovom zobrazení písma na monitoroch typu LCD, možnostiach a problémoch, ktoré tento typ zobrazenia prináša. Obsahuje popis implementácie demonštračného programu, ktorý vykresluje písmo pomocou sub-pixelov.
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Genetic Algorithm Acceleration Using OpenCL
Hrušovský, Marek ; Šimek, Václav (oponent) ; Jaroš, Jiří (vedoucí práce)
This thesis tries to accelerate genetic algorithm (GA) using OpenCL standard. Acceleration is important for the industry that solves complex problems suitable for GA. The first part of the work contains theoretical background that is needed to understand the topic of parallelization GA and the OpenCL standard. The N-queens problem was chosen to demonstrate the capabilities of accelerating permutation genetic algorithm using the OpenCL standard. The designed model uses for acceleration two GPU cards. The last part of the work deals with benchmarking the parts that are important for GA. One random generator on the GPU is approximately 80 times faster than parallel version on the CPU. One evaluation method can be up to 8000 times faster on the GPU than on the CPU. The crossover functions did not obtain any significant speed-up. However, the parts are capable to obtain speed-ups but due to selection and crossover genetic algorithm operator the whole run of parallel GA on the GPU is maximally twice as fast as on the CPU.
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