Functionality and Performance Visualization of the Distributed High Quality Volume Renderer (HVR)
Permanent link to this recordhttp://hdl.handle.net/10754/244574
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AbstractVolume rendering systems are designed to provide means to enable scientists and a variety of experts to interactively explore volume data through 3D views of the volume. However, volume rendering techniques are computationally intensive tasks. Moreover, parallel distributed volume rendering systems and multi-threading architectures were suggested as natural solutions to provide an acceptable volume rendering performance for very large volume data sizes, such as Electron Microscopy data (EM). This in turn adds another level of complexity when developing and manipulating volume rendering systems. Given that distributed parallel volume rendering systems are among the most complex systems to develop, trace and debug, it is obvious that traditional debugging tools do not provide enough support. As a consequence, there is a great demand to provide tools that are able to facilitate the manipulation of such systems. This can be achieved by utilizing the power of compute graphics in designing visual representations that reflect how the system works and that visualize the current performance state of the system.The work presented is categorized within the field of software Visualization, where Visualization is used to serve visualizing and understanding various software. In this thesis, a number of visual representations that reflect a number of functionality and performance aspects of the distributed HVR, a high quality volume renderer system that uses various techniques to visualize large volume sizes interactively. This work is provided to visualize different stages of the parallel volume rendering pipeline of HVR. This is along with means of performance analysis through a number of flexible and dynamic visualizations that reflect the current state of the system and enables manipulation of them at runtime. Those visualization are aimed to facilitate debugging, understanding and analyzing the distributed HVR.