Skip to main content

A Join Optimization Method for CPU/MIC Heterogeneous Systems

  • Conference paper
  • First Online:
Web-Age Information Management (WAIM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9659))

Included in the following conference series:

Abstract

In recent years, heterogeneous systems consisting of general CPUs and many-core coprocessors have become the main trend in the high-performance computing area due to their powerful parallel computing capabilities and superior energy efficiencies. Join is one of the most important operations in database system. In order to effectively exploit each hardware’s advantages in heterogeneous systems, in this paper we focus on how to optimize the join algorithm in hybrid CPU/MIC system. We design a join method with CPU and MIC working collaboratively when implementing the join operation. In order to fully utilize the MIC’s parallel computing power, we also propose a Sort-Scatter-Join (SSJ) algorithm for MIC to generate the join index. Through turning the traditional process of comparison and matching into the process of computing and scattering, the SSJ gains more beneficial from thread-level parallelism and SIMD data parallelism. Experiment results show that, compared with the traditional parallel sort-merge join algorithm, the peak performance of the SSJ running on MIC is improved by around 26 %.

This work is supported by National Basic Research Program of China (973) (No. 2014CB340403, No. 2012CB316205), National High Technology Research and Development Program of China (863) (No. 2014AA015204) and NSFC under the grant No. 61272137, 61033010, 61202114 and NSSFC (No. 12\&ZD220), and the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (15XNH113, 15XNLQ06). It is also supported by Huawei Innovation Research Program (No. HIRP 20140507).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Casper, J., Olukotun, K.: Hardware acceleration of database operations. In: Proceedings of the ACM/SIGDA International Symposium on FPGA, pp. 151–160. ACM, New York (2014)

    Google Scholar 

  2. Stuart, O., Brian, R., Ziliang, Z.: SQLPhi: a SQL-based database engine for Intel Xeon Phi coprocessors. In: Proceedings of the 2014 International Conference on Big Data Science and Computing, pp. 1–6. ACM Press, New York (2014)

    Google Scholar 

  3. Blanas, S., Li, Y., Patel, J.M.: Design and evaluation of main memory hash join algorithms for multi-core CPUs. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 37–48, New York (2011)

    Google Scholar 

  4. Balkesen, C., Alonso, G., Teubner, J. et al.: Multi-core, main-memory joins: sort vs. hash revisited. In: The 40th International Conference on Very Large Data Bases, pp. 85–96, Hangzhou (2014)

    Google Scholar 

  5. Kim, C., Sedlar, E., Chhugani, J., et al.: Sort vs. hash revisited fast join implementation on modern multi-core CPUs. VLDB Endow. 2(2), 1378–1389 (2009)

    Article  Google Scholar 

  6. Albutiu, M.C., Kemper, A., Neumann, T.: Massively parallel sort-merge joins in main memory multi-core database systems. VLDB Endow. 5(10), 1064–1075 (2012)

    Article  Google Scholar 

  7. He, B., Lu, M., Yang, K.: Relational query co-processing on graphics processors. Trans. Database Syst. ACM 34(4), 23–32 (2009)

    Article  Google Scholar 

  8. He, B., Yang, K., et al.: Relational joins on graphics processors. In: ACM SIGMOD International Conference on Management of Data, pp. 511–524. ACM, New York (2008)

    Google Scholar 

  9. Kaldewey, T., Lohman, G., et al.: GPU join processing revisited. In: Proceedings of the 18th International Workshop on Data Management on New Hardware, pp. 55–62 (2012)

    Google Scholar 

  10. Pirk, H., Kersten, M., Manegold, S.: Accelerating foreign-key joins using asymmetric memory channels. In: The 2nd International Conference on Accelerating Data Management Systems (2011)

    Google Scholar 

  11. Karnagel, T., Habich, D., Schlegel, B., et al.: Heterogeneity-aware operator placement in column-store DBMS. Datenbank-Spektrum 14(3), 211–221 (2014)

    Article  Google Scholar 

  12. Jim, J., James, R.: Intel Xeon Phi Coprocessor High Performance Programming. Morgan Kaufmann, San Francisco (2013)

    Google Scholar 

  13. Jha, S., He, B., Lu, M., et al.: Improving main memory hash joins on Intel Xeon Phi processors: an experimental approach. VLDB Endow. 8(6), 642–653 (2015)

    Article  Google Scholar 

  14. Tian, X., Saito, H., Preis, S.V., et al.: Effective SIMD vectorization for Intel Xeon Phi coprocessors. Sci. Program. 2015, 1–14 (2015)

    Google Scholar 

  15. Potluri, S., Venkatesh, A., et al.: Efficient intra-node communication on Intel-MIC clusters. In: The 13th IEEE/ACM Cluster, Cloud and Grid Computing, pp. 128–135 (2013)

    Google Scholar 

  16. Satish, N., Harris, M., Garland, M.: Designing efficient sorting algorithms for manycore GPUs. In: The 23rd IEEE International Symposium on Parallel and Distributed Processing, pp. 1–10 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hong Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Zhou, K., Chen, H., Sun, H., Li, C., Wu, T. (2016). A Join Optimization Method for CPU/MIC Heterogeneous Systems. In: Cui, B., Zhang, N., Xu, J., Lian, X., Liu, D. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9659. Springer, Cham. https://doi.org/10.1007/978-3-319-39958-4_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-39958-4_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39957-7

  • Online ISBN: 978-3-319-39958-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics