Prof. Dr. André Hinkenjann
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Rendering techniques for design evaluation and review or for visualizing large volume data often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates. A view direction based rendering technique renders the users central field of view in high quality whereas the surrounding is rendered with a level of detail approach depending on the distance to the users central field of view thus giving the opportunity to increase rendering efficiency. We propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.
Improving data acquisition techniques and rising computational power keep producing more and larger data sets that need to be analyzed. These data sets usually do not fit into a GPU's memory. To interactively visualize such data with direct volume rendering, sophisticated techniques for problem domain decomposition, memory management and rendering have to be used. The volume renderer Volt is used to show how CUDA is efficiently utilised to manage the volume data and a GPU's memory with the aim of low opacity volume renderings of large volumes at interactive frame rates.
In contrast to projection-based systems, large, high resolution multi-display systems offer a high pixel density on a large visualization area. This enables users to step up to the displays and see a small but highly detailed area. If the users move back a few steps they don't perceive details at pixel level but will instead get an overview of the whole visualization. Rendering techniques for design evaluation and review or for visualizing large volume data (e.g. Big Data applications) often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates.
A view direction based (VDB) rendering technique renders the user's central field of view in high quality whereas the surrounding is rendered with a level-of-detail approach depending on the distance to the user's central field of view. This approach mimics the physiology of the human eye and conserves the advantage of highly detailed information when standing close to the multi-display system as well as the general overview of the whole scene. In this paper we propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.
This article describes an approach to rapidly prototype the parameters of a Java application run on the IBM J9 Virtual Machine in order to improve its performance. It works by analyzing VM output and searching for behavioral patterns. These patterns are matched against a list of known patterns for which rules exist that specify how to adapt the VM to a given application. Adapting the application is done by adding parameters and changing existing ones. The process is fully automated and carried out by a toolkit. The toolkit iteratively cycles through multiple possible parameter sets, benchmarks them and proposes the best alternative to the user. The user can, without any prior knowledge about the Java application or the VM improve the performance of the deployed application and quickly cycle through a multitude of different settings to benchmark them. When tested with the representative benchmarks, improvements of up to 150% were achieved.