Abstract
Aiming at the low utilization rate of intensive computing cores in large heterogeneous clusters and the high complexity of collaborative computing between GPU and multi-core CPUs, this paper aims to improve resource utilization and reduce programming complexity in heterogeneous clusters. A new heterogeneous cluster cooperative computing model and engine design scheme are proposed. The complexity of communication between nodes and cooperative mechanism within nodes is analyzed. Coarse-grained cooperative execution plan is represented by template technology, and fine-grained cooperative computing plan is created by finite automata. The experimental results validate the effectiveness of the collaborative engine. Comparing with the manual programming scheme, it is found that the computational performance loss is less than 4.2%. The collaborative computing engine can effectively improve the resource utilization of large-scale heterogeneous clusters and the programming efficiency of ordinary developers.
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Acknowledgements
This work was supported in part by the Shandong Province Key Research and Development Program of China (No. 2018GGX101005), the Shandong Province Natural Science Foundation, China (No. ZR2017MF050).
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Zhao, H., Wang, H. (2021). Design of Collaboration Engine for Large-Scale Heterogeneous Clusters. 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_1
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DOI: https://doi.org/10.1007/978-981-15-3753-0_1
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