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Parallelisation of Ultrasound Simulations Using Local Fourier Decomposition
Dohnal, Matěj ; Hrbáček, Radek (referee) ; Jaroš, Jiří (advisor)
This document introduces a brand new method of the 1D, 2D and 3D decomposition with the use of local Fourier basis, its implementation and comparison with the currently used global 1D domain decomposition. The new method was designed, implemented and tested primarily for future use in the simulation software called The k-Wave toolbox, but it can be applied in many other spectral methods. Compared to the global 1D domain decomposition, the Local Fourier decomposition is up to 3 times faster and more efficient thanks to lower inter-process communication, however it is a little inaccurate. The final part of the thesis discusses the limitations of the new method and also introduces best practices to use 3D Local Fourier decomposition to achieve both more speed and accuracy.
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Detection of Deformable Marker Field
Schery, Miroslav ; Szentandrási, István (referee) ; Herout, Adam (advisor)
This Thesis is focused on study of augmented reality and creation of algorithm for a uniform marker field detector. The marker field is modified to be tolerant to a high degree of deformation. Existing marker types are studied. Important part of the paper is a description of uniform marker field technique, from which a modified assignment is derived. It also describes CUDA architecture on which the first part of the detection algorithm is implemented. Deformation tolerance, detection rate and speed tests are performed on the resulting detector algorithm.
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Parallelisation of Ultrasound Simulations Using Local Fourier Decomposition
Dohnal, Matěj ; Hrbáček, Radek (referee) ; Jaroš, Jiří (advisor)
This document introduces a brand new method of the 1D, 2D and 3D decomposition with the use of local Fourier basis, its implementation and comparison with the currently used global 1D domain decomposition. The new method was designed, implemented and tested primarily for future use in the simulation software called The k-Wave toolbox, but it can be applied in many other spectral methods. Compared to the global 1D domain decomposition, the Local Fourier decomposition is up to 3 times faster and more efficient thanks to lower inter-process communication, however it is a little inaccurate. The final part of the thesis discusses the limitations of the new method and also introduces best practices to use 3D Local Fourier decomposition to achieve both more speed and accuracy.
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