ABSTRACT
In this paper, we propose a volume rendering method using grid computing for large-scale volume image. Grid computing is attractive because medical institutions and research facilities often have a large number of idle computers. A large-scale volume image is divided into sub-volumes and the sub-volumes are rendered using grid computing. When using grid computing, different computers rarely have the same processor speeds. Thus the return order of results rarely matches the sending order. However order is vital when combining results to create a final image. Job-Scheduling is important in grid computing for volume rendering, so we use an obstacle-flag which changes priorities dynamically to manage sub-volume results. Obstacle-Flags manage visibility of each sub-volume when line of sight from the view point is obscured by other sub volumes. The proposed Dynamic Job-Scheduling based on visibility substantially increases efficiency. Our Dynamic Job- Scheduling method was implemented on our university’s campus grid and we conducted comparative experiments, which showed that the proposed method provides significant improvements in efficiency for large scale volume rendering.
TABLE OF CONTENT
TITLE PAGE
CERTIFICATION
APPROVAL
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
TABLE OF CONTENT
CHAPTER ONE
1.0 INTRODUCTION
1.1 STATEMENT OF PROBLEM
1.2 PURPOSE OF STUDY
1.3 AIMS AND OBJECTIVES
1.4 SCOPE/DELIMITATIONS
1.5 LIMITATIONS/CONSTRAINTS
1.6 DEFINITION OF TERMS
CHAPTER TWO
2.0 LITERATURE REVIEW
CHAPTER THREE
3.0 METHODS FOR FACT FINDING AND DETAILED DISCUSSIONS OF THE SYSTEM
3.1 METHODOLOGIES FOR FACT-FINDING
3.2 DISCUSSIONS
CHAPTER FOUR
4.0 FUTURES, IMPLICATIONS AND CHALLENGES OF THE SYSTEM
4.1 FUTURES
4.2 IMPLICATIONS
4.3 CHALLENGES
CHAPTER FIVE
5.0 RECOMMENDATIONS, SUMMARY AND CONCLUSION
5.1 RECOMMENDATION
5.2 SUMMARY
5.3 CONCLUSION
5.4 REFERENCES
CHAPTER ONE
1.0 INTRODUCTION
Rendering is the process of generating an image from a model (or models in what collectively could be called a scene file), by means of computer programs. A scene file contains objects in a strictly defined language or data structure; it would contain geometry, viewpoint, texture, lighting, and shading information as a description of the virtual scene. The data contained in the scene file is then passed to a rendering program to be processed and output to a digital image or raster graphics image file. The term "rendering" may be by analogy with an "artist's rendering" of a scene. Though the technical details of rendering methods vary, the general challenges to overcome in producing a 2D image from a 3D representation stored in a scene file are outlined as the graphics pipeline along a rendering device, such as a GPU. A GPU is a purpose-built device able to assist a CPU in performing complex rendering calculations. If a scene is to look relatively realistic and predictable under virtual lighting, the rendering software should solve the rendering equation. The rendering equation doesn't account for all lighting phenomena, but is a general lighting model for computer-generated imagery. 'Rendering' is also used to describe the process of calculating effects in a video editing file to produce final video output.
1.1 STATEMENT OF PROBLEM
In the case of 3D graphics, rendering may be done slowly, as in pre-rendering, or in real time. Pre-rendering is a computationally intensive process that is typically used for movie creation, while real-time rendering is often done for 3D video games which rely on the use of graphics cards with 3D hardware accelerators.
1.2 PURPOSE OF STUDY
Rendering is one of the major sub-topics of 3D computer graphics, and in practice always connected to the others. In the graphics pipeline, it is the last major step, giving the final appearance to the models and animation. With the increasing sophistication of computer graphics since the 1970s, it has become a more distinct subject.
1.3 AIMS AND OBJECTIVES
Rendering has uses in architecture, video games, simulators, movie or TV visual effects, and design visualization, each employing a different balance of features and techniques. As a product, a wide variety of renderers are available. Some are integrated into larger modeling and animation packages, some are stand-alone, some are free open-source projects. On the inside, a renderer is a carefully engineered program, based on a selective mixture of disciplines related to: light physics, visual perception, mathematics and software development.
1.4 SCOPE/DELIMITATIONS
Harnessing distributed computing resources to create a so-called render farm has therefore been a solution for animators to handle their time consuming rendering tasks. A render farm is cluster of interconnected computers which are used for rendering computer generated imagery. There are two types of rendering methods: network rendering and distributed (split-frame) rendering. In network rendering, the images can be rendered in parallel, as each frame can be calculated independently of the others. In that case, the main communication between processors is used for uploading the initial models and textures and downloading the finished images. In distributed (split-frame) rendering, each frame is divided into tiles which are rendered in parallel.
1.5 LIMITATIONS/CONSTRAINTS
A common method to save rendering time is to reduce the scene complexity but this might compromise the quality of the final animation scene. Therefore, animators often have to find a balance between the quality of the scene and the production time. However in recent years, animators were able to render highly complex 3D models for creating their animation sequences by using high performance networked computers.
1.6 DEFINITION OF TERMS
Rendering is the process of converting 3D geometric models into graphics images.
TABLE OF CONTENT
TITLE PAGE
CERTIFICATION
APPROVAL
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
TABLE OF CONTENT
CHAPTER ONE
1.0 INTRODUCTION
1.1 STATEMENT OF PROBLEM
1.2 PURPOSE OF STUDY
1.3 AIMS AND OBJECTIVES
1.4 SCOPE/DELIMITATIONS
1.5 LIMITATIONS/CONSTRAINTS
1.6 DEFINITION OF TERMS
CHAPTER TWO
2.0 LITERATURE REVIEW
CHAPTER THREE
3.0 METHODS FOR FACT FINDING AND DETAILED DISCUSSIONS OF THE SYSTEM
3.1 METHODOLOGIES FOR FACT-FINDING
3.2 DISCUSSIONS
CHAPTER FOUR
4.0 FUTURES, IMPLICATIONS AND CHALLENGES OF THE SYSTEM
4.1 FUTURES
4.2 IMPLICATIONS
4.3 CHALLENGES
CHAPTER FIVE
5.0 RECOMMENDATIONS, SUMMARY AND CONCLUSION
5.1 RECOMMENDATION
5.2 SUMMARY
5.3 CONCLUSION
5.4 REFERENCES
