Temat: NVIDIA CUDA - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Passive Radar Parallel Processing Using General-Purpose Computing on Graphics Processing Units
Autorzy:: Szczepankiewicz, K.
Malanowski, M.
Szczepankiewicz, M.
Powiązania:: https://bibliotekanauki.pl/articles/226475.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: PCL
passive coherent location
parallel implementation
NVIDIA CUDA
Opis:: In the paper an implementation of signal processing chain for a passive radar is presented. The passive radar which was developed at the Warsaw University of Technology, uses FM radio and DVB-T television transmitters as ”illuminators of opportunity”. As the computational load associated with passive radar processing is very high, NVIDIA CUDA technology has been employed for effective implementation using parallel processing. The paper contains the description of the algorithms implementation and the performance results analysis.
Źródło:: International Journal of Electronics and Telecommunications; 2015, 61, 4; 357-363
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Stereoscopic video chroma key processing using NVIDIA CUDA
Autorzy:: Sagan, J.
Powiązania:: https://bibliotekanauki.pl/articles/106272.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:: NVIDIA CUDA
chroma key processing
GPU
CPU
stereoscopic images
Opis:: In this paper, I use the NVIDIA CUDA technology to perform the chroma key algorithm on stereoscopic images. NVIDIA CUDA allows to process parallel algorithms on GPU. Input data are stereoscopic images with the monochromatic background and the destination background image. Output data is the combination of inputs by using the chroma key. I compare the algorithm efficiency between the GPU and CPU execution.
Źródło:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2013, 13, 1; 81-87
1732-1360
2083-3628
Pojawia się w:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Preconditioned Conjugate Gradient Method for Solution of Large Finite Element Problems on CPU and GPU
Autorzy:: Fialko, S. Y.
Zeglen, F.
Powiązania:: https://bibliotekanauki.pl/articles/307602.pdf
Data publikacji:: 2016
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: conjugate gradient
incomplete Cholesky factorization
iterative solvers
NVIDIA CUDA
preconditioned conjugate gradient
Opis:: In this article the preconditioned conjugate gradient (PCG) method, realized on GPU and intended to solution of large finite element problems of structural mechanics, is considered. The mathematical formulation of problem results in solution of linear equation sets with sparse symmetrical positive definite matrices. The authors use incomplete Cholesky factorization by value approach, based on technique of sparse matrices, for creation of efficient preconditioning, which ensures a stable convergence for weakly conditioned problems mentioned above. The research focuses on realization of PCG solver on GPU with using of CUBLAS and CUSPARSE libraries. Taking into account a restricted amount of GPU core memory, the efficiency and reliability of GPU PCG solver are checked and these factors are compared with data obtained with using of CPU version of this solver, working on large amount of RAM. The real-life large problems, taken from SCAD Soft collection, are considered for such a comparison.
Źródło:: Journal of Telecommunications and Information Technology; 2016, 2; 26-33
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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