Abstract
GPU heterogeneous cluster is extensively utilized in the field of data analysis and processing. Nevertheless, research and studies on collaborative activity model in computing elements of GPU heterogeneous clusters are still inadequate. To conduct research on GPU and multi-core CPU cooperative computing from a theoretical perspective, a multi-stage cooperative computing model (p-DCOT) is established. Bulk synchronous parallel (BSP) model is the core of p-DCOT. Cooperative computing is divided into three layers: data layer, computing layer and communication layer. Computing and communication are described and formalized by matrix. Lastly, representative computing examines the effectiveness of model and parameter analysis. The collaborative computing model finds out the collaborative computing in big data analysis and processing.
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Acknowledgements
This project is supported by Shandong Provincial Natural Science Foundation, China (No. ZR2017MF050), Project of Shandong Province Higher Educational Science and technology program (No. J17KA049), Shandong Province Key Research and Development Program of China (No. 2018GGX101005, 2017CXGC0701, 2016GGX109001).
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Zhang, L., Wang, H. (2021). Research on Multi-stage GPU Collaborative Model. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_2
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DOI: https://doi.org/10.1007/978-981-15-3753-0_2
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