A Simple Guideline for Code Optimizations on Modern Architectures with OpenACC and CUDA

Abstract : Learn a simple strategy guideline to optimize applications runtime. The strategy is based on four steps and illustrated on a two-dimensional Discontinuous Galerkin solver for computational fluid dynamics on structured meshes. Starting from a CPU sequential code, we guide the audience through the different steps that allowed us to increase performances on a GPU around 149 times the original runtime of the code (performances evaluated on a K20Xm). The same optimization strategy is applied to the CPU code and increases performances around 35 times the original run time (performances evaluated on a E5-1650v3 processor). Finally, different hardware architectures (Xeon CPUs, GPUs, KNL) are benchmarked with the native CUDA implementation and one based on OpenACC.
Type de document :
Communication dans un congrès
GPU Technology Conference 2017, May 2017, San Jose, United States
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https://hal-centralesupelec.archives-ouvertes.fr/hal-01527684
Contributeur : Stéphane Vialle <>
Soumis le : mardi 30 mai 2017 - 11:52:14
Dernière modification le : mardi 24 avril 2018 - 13:38:02

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  • HAL Id : hal-01527684, version 1

Citation

Ludomir Oteski, Guillaume Colin-De-Verdière, Sylvain Contassot-Vivier, Stephane Vialle, Juliet Ryan. A Simple Guideline for Code Optimizations on Modern Architectures with OpenACC and CUDA. GPU Technology Conference 2017, May 2017, San Jose, United States. 〈hal-01527684〉

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