Multi-Resolution Indexing for Hierarchical Out-of-Core Traversal of Rectilinear Grids

PDF Version Also Available for Download.

Description

The real time processing of very large volumetric meshes introduces specific algorithmic challenges due to the impossibility of fitting the input data in the main memory of a computer. The basic assumption (RAM computational model) of uniform-constant-time access to each memory location is not valid because part of the data is stored out-of-core or in external memory. The performance of most algorithms does not scale well in the transition from the in-core to the out-of-core processing conditions. The performance degradation is due to the high frequency of I/O operations that may start dominating the overall running time. Out-of-core computing [28] ... continued below

Physical Description

420 Kilobytes pages

Creation Information

Pascucci, V. July 10, 2000.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Author

Sponsor

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

The real time processing of very large volumetric meshes introduces specific algorithmic challenges due to the impossibility of fitting the input data in the main memory of a computer. The basic assumption (RAM computational model) of uniform-constant-time access to each memory location is not valid because part of the data is stored out-of-core or in external memory. The performance of most algorithms does not scale well in the transition from the in-core to the out-of-core processing conditions. The performance degradation is due to the high frequency of I/O operations that may start dominating the overall running time. Out-of-core computing [28] addresses specifically the issues of algorithm redesign and data layout restructuring to enable data access patterns with minimal performance degradation in out-of-core processing. Results in this area are also valuable in parallel and distributed computing where one has to deal with the similar issue of balancing processing time with data migration time. The solution of the out-of-core processing problem is typically divided into two parts: (i) analysis of a specific algorithm to understand its data access patterns and, when possible, redesign the algorithm to maximize their locality; and (ii) storage of the data in secondary memory with a layout consistent with the access patterns of the algorithm to amortize the cost of each I/O operation over several memory access operations. In the case of a hierarchical visualization algorithms for volumetric data the 3D input hierarchy is traversed to build derived geometric models with adaptive levels of detail. The shape of the output models is then modified dynamically with incremental updates of their level of detail. The parameters that govern this continuous modification of the output geometry are dependent on the runtime user interaction making it impossible to determine a priori what levels of detail are going to be constructed. For example they can be dependent from external parameters like the viewpoint of the current display window or from internal parameters like the isovalue of an isocontour or the position of an orthogonal slice. The structure of the access pattern can be summarized into two main points: (i) the input hierarchy is traversed level by level so that the data in the same level of resolution or in adjacent levels is traversed at the same time and (ii) within each level of resolution the data is mostly traversed at the same time in regions that are geometrically close. In this paper I introduce a new static indexing scheme that induces a data layout satisfying both requirements (i) and (ii) for the hierarchical traversal of n-dimensional regular grids. In one particular implementation the scheme exploits in a new way the recursive construction of the Z-order space filling curve. The standard indexing that maps the input nD data onto a 1D sequence for the Z-order curve is based on a simple bit interleaving operation that merges the n input indices into one index n times longer. This helps in grouping the data for geometric proximity but only for a specific level of detail. In this paper I show how this indexing can be transformed into an alternative index that allows to group the data per level of resolution first and then the data within each level per geometric proximity. This yields a data layout that is appropriate for hierarchical out-of-core processing of large grids.

Physical Description

420 Kilobytes pages

Source

  • NSF/DOE Lake Tahoe Workshop on Hierarchical Approximation and Geometrical Methods for Scientific Visualization, Tahoe City, CA (US), 10/15/2000--10/17/2000

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Report No.: UCRL-JC-140581
  • Grant Number: W-7405-Eng-48
  • Office of Scientific & Technical Information Report Number: 791074
  • Archival Resource Key: ark:/67531/metadc724429

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • July 10, 2000

Added to The UNT Digital Library

  • Sept. 29, 2015, 5:31 a.m.

Description Last Updated

  • May 6, 2016, 2:49 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 5

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Pascucci, V. Multi-Resolution Indexing for Hierarchical Out-of-Core Traversal of Rectilinear Grids, article, July 10, 2000; California. (digital.library.unt.edu/ark:/67531/metadc724429/: accessed August 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.