A modular software framework for compression of structured climate data
| Autor: | Peter Braesicke, Jörg Meyer, Jennifer Schröter, Ugur Cayoglu, Achim Streit |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science Distributed computing 020207 software engineering Usability 02 engineering and technology Modular design Space (commercial competition) 01 natural sciences Bottleneck 010305 fluids & plasmas Earth sciences Software Compression (functional analysis) 0103 physical sciences Computer data storage ddc:550 0202 electrical engineering electronic engineering information engineering business Data compression |
| Zdroj: | SIGSPATIAL/GIS |
| DOI: | 10.1145/3274895.3274897 |
| Popis: | Through the introduction of next-generation models the climate sciences have experienced a breakthrough in high-resolution simulations. In the past, the bottleneck was the numerical complexity of the models, nowadays it is the required storage space for the model output. One way to tackle the data storage challenge is through data compression. In this article we introduce a modular framework for the compression of structured climate data. Our modular framework supports the creation of individual predictors, which can be customised and adjusted to the data at hand. We provide a framework for creating interfaces and customising components, which are building blocks of individualised compression modules that are optimised for particular applications. Furthermore, the framework provides additional features such as the execution of benchmarks and validity tests for sequential as well as parallel execution of compression algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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