The atmospheric and climate sciences and the natural sciences in general are increasingly demanding for higher performance computing. Unfortunately, the gap between the diversity of the hardware architectures that the manufacturers provide to fulfill the needs for performance and the scientific modeling can't be filled by the general-purpose languages and compilers. Scientists need to manually optimize their models to exploit the machine capabilities. This leads to code redundancies when targeting different machines. This is not trivial while considering heterogeneous computing as a basis for exascale computing.
In order to provide performance portability to the icosahedral climate modeling we have developed a set of higher-level language extensions we call GGDML. The extensions provide semantically-higher-level constructs allowing to express scientific problems with scientific concepts. This eliminates the need to explicitly provide lower-level machine-dependent code. Scientists still use the general-purpose language. The GGDML code is translated by a source-to-source translation tool that optimizes the generated code to a specific machine. The translation process is driven by configurations that are provided independently from the source code.
In this poster we review some GGDML extensions and we focus mainly on the configurable code translation of the higher-level code.

@misc{IMWGJKZYDM17,
	author	 = {Nabeeh Jumah and Julian Kunkel and Günther Zängl and Hisashi Yashiro and Thomas Dubos and Yann Meurdesoif},
	title	 = {{Icosahedral Modeling with GGDML}},
	year	 = {2017},
	month	 = {10},
	location	 = {Hamburg, Germany},
	activity	 = {DKRZ user workshop 2017},
	abstract	 = {The atmospheric and climate sciences and the natural sciences in general are increasingly demanding for higher performance computing. Unfortunately, the gap between the diversity of the hardware architectures that the manufacturers provide to fulfill the needs for performance and the scientific modeling can't be filled by the general-purpose languages and compilers. Scientists need to manually optimize their models to exploit the machine capabilities. This leads to code redundancies when targeting different machines. This is not trivial while considering heterogeneous computing as a basis for exascale computing.  In order to provide performance portability to the icosahedral climate modeling we have developed a set of higher-level language extensions we call GGDML. The extensions provide semantically-higher-level constructs allowing to express scientific problems with scientific concepts. This eliminates the need to explicitly provide lower-level machine-dependent code. Scientists still use the general-purpose language. The GGDML code is translated by a source-to-source translation tool that optimizes the generated code to a specific machine. The translation process is driven by configurations that are provided independently from the source code.  In this poster we review some GGDML extensions and we focus mainly on the configurable code translation of the higher-level code.},
}