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THE IMPACT OF CUDA TECHNOLOGY ON THE EFFICIENCY OF BLENDER RENDERER PROGRAM OCENA WPŁYWU TECHNOLOGII CUDA NA WYDAJNOŚĆ PROGRAMU RENDERUJĄCEGO BLENDER

Phd Pietraszek, Kołomycki, Jacek Pietraszek, Maciej Kołomycki, Elżbieta Kocyłowska
unpublished
The paper summarizes the quantity assessment of GPU processing and supporting CUDA technology on the efficiency of BLENDER rendering program.
fatcat:k65vo2bqhbdvbd2vs6sffbttxi

THE NON-PARAMETRIC APPROACH TO THE QUANTIFICATION OF THE UNCERTAINTY IN THE DESIGN OF EXPERIMENTS MODELLING

Jacek Pietraszek, Renata Dwornicka, Mariusz Krawczyk, Maciej Kołomycki
2017 Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017)   unpublished
The classic design of experiments (DoE) typically uses the least-square method for a model identification and requires associated assumption about the normality of a noise factor. It is very convenience because it leads to a relative simple computations and well-known asymptotic statistics based on the normality assumption. However, if that assumption is not satisfied it may fail and obtained results may differ radically from the verification tests. The rationale for the caution may be the
more » ... rison of interval plots (based on the normality hypothesis) and box-plots (based on raw data). The useful approach is the bootstrap-based methodology which replaces the requirement of the normality assumption with weaker requirement of the independent and identical distribution (i.i.d.) of the random term. The industrial applications of this approach are still rare because the industry is very conservative and usually utilizes old well-known methods and typical numerical software like e.g. Statistica, Statgraphics or Minitab. This paper presents the bootstrap modeling of the random uncertainty in the two cases: the factorial designed experiment and the response surface experiment.
doi:10.7712/120217.5395.17225 fatcat:5bhezcc7jnhtrimid45mnwreme