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Algortihm Optimization Using SIMD Instructions
Sedláček, Marek ; Rydlo, Štěpán (referee) ; Orság, Filip (advisor)
This thesis talks about techniques which can be used to optimize run time of algorithms. For a demonstration of these techniques algorithms from different fields were chosen, namely particle swarm optimization, circle drawing algorithm and image (matrix) rotation algorithm. These algorithms were written in Python 3, C language and assembly language using SIMD instructions. While writing these codes emphases was placed on code efficiency. These practices were in this thesis described and compared, same as the impact on algorithm optimization. Performed tests upheld expected potential of SIMD technology for optimization, but also that this approach cannot be used in all cases. In case of circle drawing the SIMD approach achieved more than ten times better speeds than the serial implementation in C and more than one thousand times better speed than Python 3 implementation. In case of particle swarm optimization the result was opposite -- serial C implementation achieved a better speed than SIMD implementation.
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Analysis of several acceleration techniques for life insurance liability value determination
Drahokoupil, Matěj ; Pešta, Michal (advisor) ; Branda, Martin (referee)
The aim of the diploma thesis is to apprise the reader with a basic life insur- ance projection method which is used for the valuation of insurance company's liabilities. The basic projection method can be extremely time consuming in practise so another two variance reduction methods and their combination are presented to obtain either more precise liabilities estimation, or to reduce the time required for the projection. The presented methods are antithetic variate method, control-variate method and their combination later called integrated control-variate method. The final outcome of the thesis is simulation experi- ment which evaluates the liabilities of the group of policies and comparison of the presented variance reduction methods. 1
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Analysis of several acceleration techniques for life insurance liability value determination
Drahokoupil, Matěj ; Pešta, Michal (advisor) ; Branda, Martin (referee)
The aim of the diploma thesis is to apprise the reader with a basic life insur- ance projection method which is used for the valuation of insurance company's liabilities. The basic projection method can be extremely time consuming in practise so another two variance reduction methods and their combination are presented to obtain either more precise liabilities estimation, or to reduce the time required for the projection. The presented methods are antithetic variate method, control-variate method and their combination later called integrated control-variate method. The final outcome of the thesis is simulation experi- ment which evaluates the liabilities of the group of policies and comparison of the presented variance reduction methods. 1
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Algortihm Optimization Using SIMD Instructions
Sedláček, Marek ; Rydlo, Štěpán (referee) ; Orság, Filip (advisor)
This thesis talks about techniques which can be used to optimize run time of algorithms. For a demonstration of these techniques algorithms from different fields were chosen, namely particle swarm optimization, circle drawing algorithm and image (matrix) rotation algorithm. These algorithms were written in Python 3, C language and assembly language using SIMD instructions. While writing these codes emphases was placed on code efficiency. These practices were in this thesis described and compared, same as the impact on algorithm optimization. Performed tests upheld expected potential of SIMD technology for optimization, but also that this approach cannot be used in all cases. In case of circle drawing the SIMD approach achieved more than ten times better speeds than the serial implementation in C and more than one thousand times better speed than Python 3 implementation. In case of particle swarm optimization the result was opposite -- serial C implementation achieved a better speed than SIMD implementation.
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