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HyperFatTree: A Large-Scale Tree-Based Network with Low-Radix Switches

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Abstract

To lower the large-scale network cost and energy consumption, we proposed a hierarchical topology with low-radix switches. The hierarchical topology HyperFatTree is designed by combining Fat Tree topology and complete graph topology. Theory analysis of topology characteristic shows that the proposed topology can achieve high cost performance and high scalability. According to the characteristic of HyperFatTree, we designed a minimum path routing algorithm and a load balanced non-minimum path random routing algorithm for the WorstCase traffic. Evaluation shows that the saturated throughput of HyperFatTree is nearly 68.5 % at the scale of 83,232 nodes under Uniform Random traffic, which is higher than both Fat Tree and Dragonfly. It is also important that the throughput reduces only 5 % while the scale has increased 80 times, which shows good smooth scalability. Evaluation on energy efficiency shows that HyperFatTree performs better than Fat Tree and can achieve 3–7 times higher energy efficiency than Dragonfly.

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Acknowledgments

This Project is supported by the National Natural Science Foundation of China (Grant No. 61572464) and the National High Technology Research and Development Program of China (863 Program) (Grant No. 2015AA01A301).

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Authors and Affiliations

  1. State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Yong Su, Zhan Wang, Zhiguo Fan, Zheng Cao, Xiaoli Liu, En Shao, Xuejun An & Ninghui Sun

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  1. Yong Su
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  2. Zhan Wang
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  3. Zhiguo Fan
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  4. Zheng Cao
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  5. Xiaoli Liu
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  7. Xuejun An
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  8. Ninghui Sun
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Correspondence to Zheng Cao.

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Su, Y., Wang, Z., Fan, Z. et al. HyperFatTree: A Large-Scale Tree-Based Network with Low-Radix Switches. Int J Parallel Prog 45, 172–184 (2017). https://doi.org/10.1007/s10766-015-0393-2

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  • DOI: https://doi.org/10.1007/s10766-015-0393-2

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