Reducing the memory usage of structured grid solvers with wavelet compression

\nThis paper presents a new solution to address the challenge of increasing memory usage in high-performance computing simulations on structured grids. Our approach utilizes a lossy compression scheme based on the Discrete Wavelet Transform (DWT) to achieve high compression ratios while preserving the accuracy of the simulation. Our evaluation on a finite volume scheme demonstrates that the approach can reduce memory usage by several orders of magnitude.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-11-18
DOI
https://doi.org/10.1051/proc/202477079/pdf
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
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article

Reducing the memory usage of structured grid solvers with wavelet compression

Springer Link (Chiba Institute of Technology)
Mycorrhizal Fungi and Plant Interactions
article

Reducing the memory usage of structured grid solvers with wavelet compression

article en

Abstract

\nThis paper presents a new solution to address the challenge of increasing memory usage in high-performance computing simulations on structured grids. Our approach utilizes a lossy compression scheme based on the Discrete Wavelet Transform (DWT) to achieve high compression ratios while preserving the accuracy of the simulation. Our evaluation on a finite volume scheme demonstrates that the approach can reduce memory usage by several orders of magnitude.\n

Springer Link (Chiba Institute of Technology)
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Mycorrhizal Fungi and Plant Interactions
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Reducing the memory usage of structured grid solvers with wavelet compression · Springer Link (Chiba Institute of Technology) (2024) | TGRS Research Map | TGRS