Parallel and Streaming Generation of Ghost Data for Structured Grids

  • Authors:
  • Martin Isenburg;Peter Lindstrom;Hank Childs

  • Affiliations:
  • LLNL, Livermore;Lawrence Livermore National Laboratory, Livermore;Lawrence Berkeley Labs, Berkeley

  • Venue:
  • IEEE Computer Graphics and Applications
  • Year:
  • 2010

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Abstract

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.