Single-pass GPU-raycasting for structured adaptive mesh refinement data

Ralf Kaehler; Tom Abel

doi:10.1117/12.2008552

4 February 2013 Single-pass GPU-raycasting for structured adaptive mesh refinement data

Ralf Kaehler, Tom Abel

Proceedings Volume 8654, Visualization and Data Analysis 2013; 865408 (2013) https://doi.org/10.1117/12.2008552
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

Structured Adaptive Mesh Refinement (SAMR) is a popular numerical technique to study processes with high spatial and temporal dynamic range. It reduces computational requirements by adapting the lattice on which the underlying differential equations are solved to most efficiently represent the solution. Particularly in astrophysics and cosmology such simulations now can capture spatial scales ten orders of magnitude apart and more. The irregular locations and extensions of the refined regions in the SAMR scheme and the fact that different resolution levels partially overlap, poses a challenge for GPU-based direct volume rendering methods. kD-trees have proven to be advantageous to subdivide the data domain into non-overlapping blocks of equally sized cells, optimal for the texture units of current graphics hardware, but previous GPU-supported raycasting approaches for SAMR data using this data structure required a separate rendering pass for each node, preventing the application of many advanced lighting schemes that require simultaneous access to more than one block of cells. In this paper we present the first single-pass GPU-raycasting algorithm for SAMR data that is based on a kD-tree. The tree is efficiently encoded by a set of 3D-textures, which allows to adaptively sample complete rays entirely on the GPU without any CPU interaction. We discuss two different data storage strategies to access the grid data on the GPU and apply them to several datasets to prove the benefits of the proposed method.

Citation Download Citation

Ralf Kaehler and Tom Abel "Single-pass GPU-raycasting for structured adaptive mesh refinement data", Proc. SPIE 8654, Visualization and Data Analysis 2013, 865408 (4 February 2013); https://doi.org/10.1117/12.2008552

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available