SoftwareX (Dec 2023)

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

  • Qian Gong,
  • Jieyang Chen,
  • Ben Whitney,
  • Xin Liang,
  • Viktor Reshniak,
  • Tania Banerjee,
  • Jaemoon Lee,
  • Anand Rangarajan,
  • Lipeng Wan,
  • Nicolas Vidal,
  • Qing Liu,
  • Ana Gainaru,
  • Norbert Podhorszki,
  • Richard Archibald,
  • Sanjay Ranka,
  • Scott Klasky

Journal volume & issue
Vol. 24
p. 101590

Abstract

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We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids. With exceptional data compression capability and precise error control, MGARD addresses a wide range of requirements, including storage reduction, high-performance I/O, and in-situ data analysis. It features a unified application programming interface (API) that seamlessly operates across diverse computing architectures. MGARD has been optimized with highly-tuned GPU kernels and efficient memory and device management mechanisms, ensuring scalable and rapid operations.

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