Sort-first parallel volume rendering

A Distributed Memory Hierarchy and Data Management for Interactive Scene Navigation and Modification on Tiled Display Walls

Simultaneous modification and navigation of massive 3D models are difficult because repeated data edits affect the data layout and coherency on a secondary storage, which in turn affect the interactive out-of-core rendering performance. In this paper, we propose a novel approach for distributed data management for simultaneous interactive navigation and modification of massive 3D data using the readily available infrastructure of a tiled display. Tiled multi-displays, projection or LCD panel based, driven by a PC cluster, can be viewed as a cluster of storage-compute-display (SCD) nodes. Given a cluster of SCD node infrastructure, we first propose a distributed memory hierarchy for interactive rendering applications. Second, in order to further reduce the latency in such applications, we propose a new data partitioning approach for distributed storage among the SCD nodes that reduces the variance in the data load across the SCD nodes. Our data distribution method takes in a data set of any size, and reorganizes it into smaller partitions, and stores it across the multiple SCD nodes. These nodes store, manage, and coordinate data with other SCD nodes to simultaneously achieve interactive navigation and modification. Specifically, the data is not duplicated across these distributed secondary storage devices. In addition, coherency in data access, due to screen-space adjacency of adjacent displays in the tile, as well as object space adjacency of the data sets, is well leveraged in the design of the data management technique. Empirical evaluation on two large data sets, with different data density distribution, demonstrates that the proposed data management approach achieves superior performance over alternative state-of-the-art methods.

Low-Pass Filtered Volumetric Shadows

We present a novel and efficient method to compute volumetric soft shadows for interactive direct volume visualization to improve the perception of spatial depth. By direct control of the softness of volumetric shadows, disturbing visual patterns due to hard shadows can be avoided and users can adapt the illumination to their personal and application-specific requirements. We compute the shadowing of a point in the data set by employing spatial filtering of the optical depth over a finite area patch pointing toward each light source. Conceptually, the area patch spans a volumetric region that is sampled with shadow rays; afterward, the resulting optical depth values are convolved with a low-pass filter on the patch. In the numerical computation, however, to avoid expensive shadow ray marching, we show how to align and set up summed area tables for both directional and point light sources. Once computed, the summed area tables enable efficient evaluation of soft shadows for each point in constant time without shadow ray marching and the softness of the shadows can be controlled interactively. We integrated our method in a GPU-based volume renderer with ray casting from the camera, which offers interactive control of the transfer function, light source positions, and viewpoint, for both static and time-dependent data sets. Our results demonstrate the benefit of soft shadows for visualization to achieve user-controlled illumination with many-point lighting setups for improved perception combined with high rendering speed.

Turbulence Visualization at the Terascale on Desktop PCs

Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small- and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume.

Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography

The 3D visualization of astronomical nebulae is a challenging problem since only a single 2D projection is observable from our fixed vantage point on Earth. We attempt to generate plausible and realistic looking volumetric visualizations via a tomographic approach that exploits the spherical or axial symmetry prevalent in some relevant types of nebulae. Different types of symmetry can be implemented by using different randomized distributions of virtual cameras. Our approach is based on an iterative compressed sensing reconstruction algorithm that we extend with support for position-dependent volumetric regularization and linear equality constraints. We present a distributed multi-GPU implementation that is capable of reconstructing high-resolution datasets from arbitrary projections. Its robustness and scalability are demonstrated for astronomical imagery from the Hubble Space Telescope. The resulting volumetric data is visualized using direct volume rendering. Compared to previous approaches, our method preserves a much higher amount of detail and visual variety in the 3D visualization, especially for objects with only approximate symmetry.

Image plane sweep volume illumination

In recent years, many volumetric illumination models have been proposed, which have the potential to simulate advanced lighting effects and thus support improved image comprehension. Although volume ray-casting is widely accepted as the volume rendering technique which achieves the highest image quality, so far no volumetric illumination algorithm has been designed to be directly incorporated into the ray-casting process. In this paper we propose image plane sweep volume illumination (IPSVI), which allows the integration of advanced illumination effects into a GPU-based volume ray-caster by exploiting the plane sweep paradigm. Thus, we are able to reduce the problem complexity and achieve interactive frame rates, while supporting scattering as well as shadowing. Since all illumination computations are performed directly within a single rendering pass, IPSVI does not require any preprocessing nor does it need to store intermediate results within an illumination volume. It therefore has a significantly lower memory footprint than other techniques. This makes IPSVI directly applicable to large data sets. Furthermore, the integration into a GPU-based ray-caster allows for high image quality as well as improved rendering performance by exploiting early ray termination. This paper discusses the theory behind IPSVI, describes its implementation, demonstrates its visual results and provides performance measurements.