MATEC Web Conf.
Volume 208, 20182018 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018)
|Number of page(s)||6|
|Section||Computer Science and Intelligent Technology|
|Published online||26 September 2018|
An Early Performance Comparison of CUDA and OpenACC
Department of Computer Science, Concordia University Chicago, River Forest IL, USA
2 Institute of Industrial and Business Management, National Taipei University of Technology, Taipei, Taiwan
This paper presents a performance comparison between CUDA and OpenACC. The performance analysis focuses on programming models and underlying compilers. In addition, we proposed a Performance Ratio of Data Sensitivity (PRoDS) metric to objectively compare traditional subjective performances: how sensitive OpenACC and CUDA implementations are to change in data size. The results show that in terms of kernel running time, the OpenACC performance is lower than the CUDA performance because PGI compiler needs to translate OpenACC kernels into object code while CUDA codes can be directly run. Besides, OpenACC programs are more sensitive to data changes than the equivalent CUDA programs with optimizations, but CUDA is more sensitive to data changes than OpenACC if there are no optimizations. Overall we found that OpenACC is a reliable programming model and a good alternative to CUDA for accelerator devices.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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