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A New CPU-FPGA Heterogeneous gStore System

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Web and Big Data (APWeb-WAIM 2020)

Abstract

In this demonstration, we present a new CPU-FPGA heterogeneous gStore system. The previous gStore system is based on CPU and has low join query performance when the data size is too big. We implement a FPGA-based join module to speed up join queries. Furthermore, we design a FPGA-friendly data structure called FFCSR to facilitate it. We compare our new system with the previous one on the LUBM2B dataset. Experimental results demonstrate that the new CPU-FPGA heterogeneous system performs better than the previous one based on CPU.

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References

  1. Alam, M., Perumalla, K.S., Sanders, P.: Novel parallel algorithms for fast multi-GPU-based generation of massive scale-free networks. Data Sci. Eng. 4(1), 61–75 (2019). https://doi.org/10.1007/s41019-019-0088-6

    Article  Google Scholar 

  2. Ngo, H.Q., Porat, E., Ré, C., Rudra, A.: Worst-case optimal join algorithms. J. ACM (JACM) 65(3), 16 (2018)

    Article  MathSciNet  Google Scholar 

  3. Shen, X., et al.: A graph-based RDF triple store. In: 2015 IEEE 31st International Conference on Data Engineering, pp. 1508–1511. IEEE (2015)

    Google Scholar 

  4. Zeng, L., Zou, L., Özsu, M.T., Hu, L., Zhang, F.: GSI: GPU-friendly subgraph isomorphism. arXiv preprint arXiv:1906.03420 (2019)

  5. Zhou, S., Prasanna, V.K.: Accelerating graph analytics on CPU-FPGA heterogeneous platform. In: 2017 29th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pp. 137–144. IEEE (2017)

    Google Scholar 

  6. Zou, L., Mo, J., Chen, L., Özsu, M.T., Zhao, D.: gStore: answering SPARQL queries via subgraph matching. Proc. VLDB Endow. 4(8), 482–493 (2011)

    Article  Google Scholar 

  7. Zou, L., Özsu, M.T., Chen, L., Shen, X., Huang, R., Zhao, D.: gStore: a graph-based SPARQL query engine. VLDB J.-Int. J. Very Large Data Bases 23(4), 565–590 (2014)

    Article  Google Scholar 

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Acknowledgment

This work was supported by The National Key Research and Development Program of China under grant 2018YFB1003504 and NSFC under grant 61932001.

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Correspondence to Lei Zou .

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Su, X., Lin, Y., Zou, L. (2020). A New CPU-FPGA Heterogeneous gStore System. In: Wang, X., Zhang, R., Lee, YK., Sun, L., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2020. Lecture Notes in Computer Science(), vol 12318. Springer, Cham. https://doi.org/10.1007/978-3-030-60290-1_39

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  • DOI: https://doi.org/10.1007/978-3-030-60290-1_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60289-5

  • Online ISBN: 978-3-030-60290-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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