Rinne, T., 2014. Efficient evaluation of functionally represented volumetric objects. Masters Thesis (Masters). Bournemouth University.
Full text available as:
|
PDF
Rinne,Tuomo_MRes_2014.pdf 1MB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Abstract
There are several approaches to representing shapes in computer graphics. One of the ways to describe objects and operations is Function Representation (FRep). In FRep, a geometric object is de ned by a single continuous real-valued function of point coordinates. Generally geometric modelling is conducted in order to achieve visual outcome. In FRep the transformation of a function into a visual representation relies on extensive sampling of the function. The computational cost of the sampling can cause adverse e ects during applications runtime. In this thesis the problem of e cient evaluation of the de ning function is discussed. An observation is made on wide range of operations and primitives within FRep and their suitability for parallelization. Furthermore, a new novel method is proposed to distribute FReps computational workloads on parallel hardware devices such as graphics programming units and multi-core processors.
Item Type: | Thesis (Masters) |
---|---|
Additional Information: | If you feel that this work infringes your copyright please contact the BURO Manager. |
Uncontrolled Keywords: | Scalar fields ; Heterogeneous computing ; Function respresentation ; High-performance computing |
Group: | Faculty of Media & Communication |
ID Code: | 22562 |
Deposited By: | Symplectic RT2 |
Deposited On: | 29 Sep 2015 09:52 |
Last Modified: | 14 Mar 2022 13:53 |
Downloads
Downloads per month over past year
Repository Staff Only - |