https://github.com/dlr-amr/cmc

Lossy and lossless compression of geo-spatial ESM simulation data based on adaptive mesh refinement
https://github.com/dlr-amr/cmc

Last synced: 6 months ago
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Lossy and lossless compression of geo-spatial ESM simulation data based on adaptive mesh refinement

• Host: GitHub
• URL: https://github.com/dlr-amr/cmc
• Owner: DLR-AMR
• License: other
• Created: 2023-01-20T08:54:56.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-06-05T11:48:45.000Z (7 months ago)
• Last Synced: 2025-06-05T12:35:46.502Z (7 months ago)
• Language: C++
• Homepage:
• Size: 1.01 MB
• Stars: 5
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: ChangeLog
  • License: COPYING
  • Authors: AUTHORS

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README

          

### !Currently, the repository is under construction and some functionality might not work as expected! 

### Introduction

CMC is a software package providing data compression techniques based on methods of the field of adaptive mesh refinement (AMR).  

It is especially suited for geo-spatial data originating for example from Earth System Model (ESM) simulations.  

CMC can be used either as a post-processing tool in order to read and compress data from netCDF files or it can be directly linked to simulation codes in order to perform an online compression.  

Interfaces for C and Fortran codes as well as several further compression approaches are underway.  

The capabilities of CMC encompass compression based on point-wise absolute and relative error critera. Moreover, splitting of higher dimensional data into several lower dimensional data slices is provided alongside the opportunity to formulate region-wise varying error thresholds for the compression to comply to - that includes in particular nested error domains.  

Besides the opportunity to perform lossy compression, a lossless compression mode is available as well.  

CMC uses [t8code](https://github.com/DLR-AMR/t8code) as its underlying AMR engine, which allows for broad variety of applications, since t8code provides a highly parallel and scalable AMR implementation of various element types.