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

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring
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MGARD:用于高性能、错误控制数据压缩和重构的多重网格框架

DOI:
10.1016/j.softx.2023.101590
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发表时间:
2023
期刊:
影响因子:
3.4
通讯作者:
Vidal, Nicolas
Vidal, Nicolas
中科院分区:
计算机科学4区
文献类型:
--
作者:
Gong, Qian;Chen, Jieyang;Whitney, Ben;Liang, Xin;Reshniak, Viktor;Banerjee, Tania;Lee, Jaemoon;Rangarajan, Anand;Wan, Lipeng;Vidal, Nicolas

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我们描述了MGARD,一个软件提供多网格自适应减少浮点科学数据的结构化和非结构化网格。凭借卓越的数据压缩能力和精确的错误控制,MGARD可满足各种需求,包括减少存储、高性能I/O和原位数据分析。它具有统一的应用程序编程接口(API),可在不同的计算架构中无缝运行。MGARD已通过高度调整的GPU内核和高效的内存和设备管理机制进行了优化,确保可扩展和快速操作。
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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