17723

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki
Tokyo Institute of Technology
arXiv:1710.08616 [cs.DC], (24 Oct 2017)

@article{muller2017hybrid,

   title={Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model},

   author={Muller, Michel and Aoki, Takayuki},

   year={2017},

   month={oct},

   archivePrefix={"arXiv"},

   primaryClass={cs.DC}

}

In this work we use the GPU porting task for the operative Japanese weather prediction model "ASUCA" as an opportunity to examine productivity issues with OpenACC when applied to structured grid problems. We then propose "Hybrid Fortran", an approach that combines the advantages of directive based methods (no rewrite of existing code necessary) with that of stencil DSLs (memory layout is abstracted). This gives the ability to define multiple parallelizations with different granularities in the same code. Without compromising on performance, this approach enables a major reduction in the code changes required to achieve a hybrid GPU/CPU parallelization – as demonstrated with our ASUCA implementation using Hybrid Fortran.
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