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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 874Factorial Approach to Assessment of GPU...

Factorial Approach to Assessment of GPU Computational Efficiency in Surrogate Models

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Abstract:

Surrogate models are very useful to replace very accurate but time-consuming huge data numerical models. The process of construction and optimization of surrogate models may require large computational power. It may be delivered by multi-core CPU or by massively multi-core GPGPU. This paper presents a consistent approach to make quantitative assessment of the computational efficiency with different hardware configurations: with one and multi-core CPU and with GPGPU card. The design of experiments factorial approach is used to analysis of the obtained data. The linear main effects model with two-way interaction is identified. The results show that the investment to multi-core CPU and GPGPU cards simultaneously is impractical due to negligible effects of CPU efficiency which is masked by dominated GPGPU performance.

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Periodical:

Advanced Materials Research (Volume 874)

Pages:

157-162

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.874.157

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Online since:

January 2014

Authors:

Jacek Pietraszek, Agnieszka Szczotok*, Elżbieta Kocyłowska

Keywords:

Design of Experiment (DOE), Factorial Approach, GPU, Surrogate Models

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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