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Fast and efficient compression of floating-point data.

Peter Lindstrom1, Martin Isenburg

  • 1Lawrence Livermore National Laboratory, USA. pl@llnl.gov

IEEE Transactions on Visualization and Computer Graphics
|November 4, 2006
PubMed
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This study introduces a novel lossless, online data compression method for scientific simulations. It significantly accelerates input/output (I/O) speeds by reducing data transfer, preventing simulation stalls.

Area of Science:

  • High-performance computing
  • Data compression
  • Scientific visualization

Background:

  • Large-scale scientific simulations face I/O bottlenecks due to growing datasets.
  • Existing compression methods often prioritize compression ratio over speed or require data quantization, unsuitable for exact value retention.

Purpose of the Study:

  • To develop a lossless, online data compression scheme for floating-point data in scientific simulations.
  • To improve I/O throughput and reduce simulation idle time.

Main Methods:

  • Implemented a simple, lossless, online compression scheme for floating-point data.
  • Integrated a plug-in for data-dependent prediction, adaptable to various data types (meshes, images, etc.).
  • Utilized an improved entropy coder for enhanced speed and compression.

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Main Results:

  • Achieved state-of-the-art compression rates and speeds.
  • Demonstrated significant acceleration of I/O throughput in real simulation runs.
  • Showcased adaptability to variable-precision floating-point and integer data.

Conclusions:

  • The proposed compression scheme effectively alleviates I/O bottlenecks in large-scale scientific simulations.
  • It offers a practical solution for lossless, high-throughput data compression without sacrificing data precision.
  • The method's flexibility makes it suitable for diverse scientific data and applications.