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GTC ON-DEMAND

Performance Optimization
Presentation
Media
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 sequ ...Read More
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.  Back
 
Topics:
Performance Optimization, Algorithms & Numerical Techniques, Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7626
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