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Abstract

Demand for high-performance computing is increasing in earth system modeling, and in natural sciences in general. Unfortunately, automatic optimizations done by compilers are not enough to make use of target machines' capabilities. Manual code adjustments are mandatory to exploit hardware capabilities. However, optimizing for one architecture, may degrade performance for other architectures. This loss of portability is a challenge. Our approach involves the use of the GGDML language extensions to write a higher-level modeling code, and use a user-controlled source-to-source translation technique. Translating the code results in an optimized version for the target machine.
The contributions of this poster are: * The use of a highly-configurable code translation technique to transform higher-level code into target-machine-optimized code. * Evaluation of code transformation for multi-core and GPU based machines, both single and multi-node configurations.

BibTeX

@misc{AUGCTTFPPO18,
	author	 = {Nabeeh Jumah and Julian Kunkel},
	title	 = {{A user-controlled GGDML Code Translation Technique for Performance Portability of Earth System Models}},
	year	 = {2018},
	month	 = {06},
	location	 = {Germany, Frankfurt},
	activity	 = {ISC 2018},
	abstract	 = {Demand for high-performance computing is increasing in earth system modeling, and in natural sciences in general. Unfortunately, automatic optimizations done by compilers are not enough to make use of target machines' capabilities. Manual code adjustments are mandatory to exploit hardware capabilities. However, optimizing for one architecture, may degrade performance for other architectures. This loss of portability is a challenge. Our approach involves the use of the GGDML language extensions to write a higher-level modeling code, and use a user-controlled source-to-source translation technique. Translating the code results in an optimized version for the target machine.  The contributions of this poster are: * The use of a highly-configurable code translation technique to transform higher-level code into target-machine-optimized code. * Evaluation of code transformation for multi-core and GPU based machines, both single and multi-node configurations.},
	url	 = {https://ssl.linklings.net/conferences/isc_hpc/assets/2018/posters/post104.pdf},
}

publication.txt · Last modified: 2019-01-23 10:26 by 127.0.0.1

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