[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Adaptive Access Path Selection for Hardware-Accelerated DRAM Loads

  • Conference paper
  • First Online:
Databases Theory and Applications (ADC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10837))

Included in the following conference series:

  • 1134 Accesses

Abstract

For modern main memory database systems, the memory bus is the main bottleneck. Specialized hardware components of large NUMA systems, such as HPE’s GRU, make it possible to offload memory transfers. In some cases, this improves the throughput by 30%, but other scenarios suffer from reduced performance. We show which factors influence this tradeoff. Based on our experiments, we present an adaptive prediction model that supports the DBMS in deciding whether to utilize these components. In addition, we evaluate non-coherent memory access as an additional access method and discuss its benefits and shortcomings.

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 35.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 44.99
Price includes VAT (United Kingdom)
  • 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

Similar content being viewed by others

Notes

  1. 1.

    All benchmarks were executed on an SGI UV 300H with 6 TB RAM and eight Intel E7-8890 v2 processors. Our code was compiled with gcc 7.2 at .

References

  1. Abadi, D.J., Madden, S., Ferreira, M.: Integrating compression and execution in column-oriented database systems. In: ACM SIGMOD International Conference on Management of Data (2006)

    Google Scholar 

  2. Boncz, P.A., Manegold, S., Kersten, M.L.: Database architecture optimized for the new bottleneck: memory access. In: 25th International Conference on Very Large Data Bases (1999)

    Google Scholar 

  3. Dreseler, M., et al.: Hardware-accelerated memory operations on large-scale NUMA systems. In: Eighth International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (ADMS) (2017)

    Google Scholar 

  4. Foong, A.P., et al.: TCP performance re-visited. In: IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) (2003)

    Google Scholar 

  5. Neumann, T., Mühlbauer, T., Kemper, A.: Fast serializable multi-version concurrency control for main-memory database systems. In: ACM SIGMOD International Conference on Management of Data (2015)

    Google Scholar 

  6. Oracle. Oracle’s SPARC T7 and SPARC M7 Server Architecture. Technical report. https://www.oracle.com/assets/sparc-t7-m7-serverarchitecture-2702877.pdf. Accessed 12 June 2017

  7. Psaroudakis, I., et al.: Adaptive NUMA-aware data placement and task scheduling for analytical workloads in main-memory column-stores. In: Proceedings of the VLDB (2016)

    Google Scholar 

  8. Thorson, G., Woodacre, M.: SGI UV2: a fused computation and data analysis machine. In: International Conference on High Performance Computing, Networking, Storage and Analysis (2012)

    Google Scholar 

  9. Ungethüm, A., et al.: Overview on hardware optimizations for database engines. In: Datenbanksysteme für Business, Technologie und Web (BTW) (2017)

    Google Scholar 

Download references

Acknowledgments

We thank Martin Boissier and Rainer Schlosser for their helpful input on the estimation model.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Markus Dreseler .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dreseler, M., Gasda, T., Kossmann, J., Uflacker, M., Plattner, H. (2018). Adaptive Access Path Selection for Hardware-Accelerated DRAM Loads. In: Wang, J., Cong, G., Chen, J., Qi, J. (eds) Databases Theory and Applications. ADC 2018. Lecture Notes in Computer Science(), vol 10837. Springer, Cham. https://doi.org/10.1007/978-3-319-92013-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92013-9_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92012-2

  • Online ISBN: 978-3-319-92013-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics