Parallel Texture-Based Vector Field Visualization on Curved Surfaces Using GPU Cluster Computers
This is a Eurographics Symposium on Parallel Graphics and Visualization (2006) paper by Sven Bachthaler, Daniel Weiskopf, Magnus Strengert and Thomas Ertl.
This paper is available for download.
We adopt a technique for texture-based visualization of flow fields on curved surfaces for parallel computation on
a GPU cluster. The underlying LIC method relies on image-space calculations and allows the user to visualize
a full 3D vector field on arbitrary and changing hypersurfaces. By using parallelization, both the visualization
speed and the maximum data set size are scaled with the number of cluster nodes. A sort-first strategy with
image-space decomposition is employed to distribute the workload for the LIC computation, while a sort-last
approach with an object-space partitioning of the vector field is used to increase the total amount of available GPU
memory. We specifically address issues for parallel GPU-based vector field visualization, such as reduced locality
of memory accesses caused by particle tracing, dynamic load balancing for changing camera parameters, and the
combination of image-space and object-space decomposition in a hybrid approach. Performance measurements
document the behavior of our implementation on a GPU cluster with AMD Opteron CPUs, NVIDIA GeForce 6800
Ultra GPUs, and Infiniband network connection.
Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Viewing algorithms I.3.3
[Three-Dimensional Graphics and Realism]: Color, shading, shadowing, and texture
Last modified: Jan. 25th, 2007
by Sven Bachthaler