Current visualization tools lack the ability to perform fullrange spatial and temporal analysis on terascale scientific datasets. Two key reasons exist for this shortcoming: I/O ...
Wesley Kendall, Markus Glatter, Jian Huang, Tom Pe...
Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering sol...
Simulations often generate large amounts of data that require use of SciVis techniques for effective exploration of simulation results. In some cases, like 1D theory of fluid dyn...
Kresimir Matkovic, Mario Jelovic, Josip Juric, Zol...
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
Parallel applications typically run in batch mode, sometimes after long waits in a scheduler queue. In some situations, it would be desirable to interactively add new functionalit...