TY - GEN
T1 - A Survey of GPU-Based Large-Scale Volume Visualization
AU - Beyer, Johanna
AU - Hadwiger, Markus
AU - Pfister, Hanspeter
N1 - Publisher Copyright:
© 2014 16th Eurographics Conference on Visualization - State of the Art Reports, EuroVis-STAR 2014. All rights reserved.
PY - 2014
Y1 - 2014
N2 - This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera-, and petabytes of volume data can be enabled on GPUS. In addition to combining the parallel processing power of GPUS with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e., "output-sensitive" algorithms and system designs. This leads to recent outputsensitive approaches that are "ray-guided," "visualization-driven," or "display-aware." In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks-the current subset of data that is minimally required to produce an output image of the desired display resolution. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we discuss in this survey. c The Eurographics Association 2014.
AB - This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera-, and petabytes of volume data can be enabled on GPUS. In addition to combining the parallel processing power of GPUS with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e., "output-sensitive" algorithms and system designs. This leads to recent outputsensitive approaches that are "ray-guided," "visualization-driven," or "display-aware." In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks-the current subset of data that is minimally required to produce an output image of the desired display resolution. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we discuss in this survey. c The Eurographics Association 2014.
UR - http://www.scopus.com/inward/record.url?scp=85123273772&partnerID=8YFLogxK
U2 - 10.2312/eurovisstar.20141175
DO - 10.2312/eurovisstar.20141175
M3 - Conference contribution
AN - SCOPUS:85123273772
T3 - 16th Eurographics Conference on Visualization - State of the Art Reports, EuroVis-STAR 2014
SP - 105
EP - 123
BT - 16th Eurographics Conference on Visualization - State of the Art Reports, EuroVis-STAR 2014
A2 - Borgo, R.
A2 - Maciejewski, R.
A2 - Viola, I.
PB - The Eurographics Association
T2 - 16th Eurographics Conference on Visualization - State of the Art Reports, EuroVis-STAR 2014
Y2 - 9 June 2014 through 13 June 2014
ER -