This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Parallel and Streaming Generation of Ghost Data for Structured Grids
May/June 2010 (vol. 30 no. 3)
pp. 32-44
Martin Isenburg, LLNL, Livermore
Peter Lindstrom, Lawrence Livermore National Laboratory, Livermore
Hank Childs, Lawrence Berkeley Labs, Berkeley
Parallel simulations decompose large domains into many blocks. A fundamental requirement for subsequent parallel analysis and visualization is the presence of ghost data that supplements each block with a layer of adjacent data elements from neighboring blocks. The standard approach for generating ghost data requires all blocks to be in memory at once. This becomes impractical when fewer processors—and thus less aggregate memory—are available for analysis than for simulation. A proposed algorithm for generating ghost data for structured grids uses many fewer processors than previously possible. It stores as little as one block per processor in memory and can run on as few processors as are available (possibly just one). The basic approach first slightly changes the original blocks' size by declaring parts of them to be ghost data and then pads adjacent blocks with this data.
Index Terms:
parallel algorithms, streaming processing, ghost data, structured grids, isocontour extraction, computer graphics, graphics and multimedia
Citation:
Martin Isenburg, Peter Lindstrom, Hank Childs, "Parallel and Streaming Generation of Ghost Data for Structured Grids," IEEE Computer Graphics and Applications, vol. 30, no. 3, pp. 32-44, May-June 2010, doi:10.1109/MCG.2010.26
Usage of this product signifies your acceptance of the Terms of Use.