Scientific data is continually increasing in complexity, variety and size, making efficient
visualization and specifically rendering an ongoing challenge. Traditional rasterization …

With the push to exascale, in situ visualization and analysis will continue to play an
important role in high performance computing. Tightly coupling in situ visualization with …

Current architectural trends on supercomputers have dramatic increases in the number of
cores and available computational power per die, but this power is increasingly difficult for …

We propose two hardware mechanisms to decrease energy consumption on massively
parallel graphics processors for ray tracing while kee** performance high. First, we use a …

We propose two hardware mechanisms to decrease energy consumption on massively
parallel graphics processors for ray tracing. First, we use a streaming data model and …

In situ visualization has become a popular method for avoiding the slowest component of
many visualization pipelines: reading data from disk. Most previous in situ work has focused …

Visualizing large molecular data requires efficient means of rendering millions of data
elements that combine glyphs, geometry and volumetric techniques. The geometric and …

Large-scale simulations can easily produce data in excess of what can be efficiently
visualized using production visualization software, making it challenging for scientists to …

CPU Ray tracing in scientific visualization has been shown to be an efficient rendering
algorithm for large-scale polygonal data on distributed-memory systems by using custom …

Ray tracing is becoming more widely adopted in offline rendering systems due to its natural
support for high quality lighting. Since quality is also a concern in most real time systems, we …