Multiscale visualizations are typically used to analyze multiscale processes and data in
various application domains, such as the visual exploration of hierarchical genome …

The unprecedented amount of scientific data has introduced heavy pressure on the current
data storage and transmission systems. Progressive compression has been proposed to …

To address the problem of ever-growing scientific data sizes making data movement a major
hindrance to analysis, we introduce a novel encoding for scalar fields: a unified tree of …

We present a technique that leverages ray tracing hardware available in recent Nvidia RTX
GPUs to solve a problem other than classical ray tracing. Specifically, we demonstrate how …

As the computation power of supercomputers increases, so does simulation size, which in
turn produces orders-of-magnitude more data. Because generated data often exceed the …

Extreme-scale simulations and high-resolution instruments have been generating an
increasing amount of data, which poses significant challenges to not only data storage …

In scientific simulations, observations, and experiments, the transfer of data to and from disk
and across networks has become a major bottleneck for data analysis and visualization …

The increasing amount of data in meteorological science requires effective data-reduction
methods. Our study demonstrates the use of advanced scientific lossy compression …

We present a novel technique for hierarchical super resolution (SR) with neural networks
(NNs), which upscales volumetric data represented with an octree data structure to a high …

Optimizing the performance of large-scale parallel codes is critical for efficient utilization of
computing resources. Code developers often explore various execution parameters, such as …