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

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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.
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Dates and versions

hal-01527684 , version 1 (30-05-2017)

Identifiers

  • HAL Id : hal-01527684 , version 1

Cite

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, NVIDIA, May 2017, San Jose, United States. ⟨hal-01527684⟩
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