Skip to main content

High Performance Stencil Computations for Intel\(^{\normalsize \circledR }\) Xeon Phi™ Coprocessor

  • Conference paper
  • First Online:
  • 918 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 626))

Abstract

Stencil computations are a class of computational kernels which update array elements according to some stencil patterns, and they have drawn more attentions recently. The Intel Xeon Phi coprocessor, which is designed for high performance computing, has not been fully evaluated for stencil computations. In this paper, we present a series of optimizations to accelerate the 3-D 7-point stencil code on Intel Xeon Phi coprocessor. We focus on how to exploit the performance potential of many cores and wide-vector unit in each core. In order to exploit data locality, we use loop tiling and we propose a method for calculating the block size while tiling. The achieved performance brings a speedup of 211.6 in comparison with the serial code.

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

Buying options

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

Learn about institutional subscriptions

References

  1. HiStencils. http://www.exastencils.org/histencils/. Accessed 15 Apr 2015

  2. Stencil code. http://en.wikipedia.org/wiki/Stencil_code/. Accessed 15 Apr 2015

  3. Michael, M., Reinders, J., Robison, A.: Structured Parallel Programming: Patterns for Efficient Computation. Elsevier, Amsterdam (2012)

    Google Scholar 

  4. Intel Corporation. Intel\(^{\textregistered }\) Xeon Phi™ coprocessor system software developers guide, March 2014

    Google Scholar 

  5. Duran, A., Michael, K.: The Intel\(^{\textregistered }\) many integrated core architecture. In: International Conference on High Performance Computing and Simulation (HPCS). IEEE (2012)

    Google Scholar 

  6. James, J., Reinders, J.: Intel\(^{\textregistered }\) Xeon Phi™ Coprocessor High-performance Programming. Newnes, Oxford (2013)

    Google Scholar 

  7. Top 500 list. http://www.top500.org/. Accessed 1 June 2016

  8. Chapman, B., Jost, G., Van Der Pas, R.: Using OpenMP: Portable Shared Memory Parallel Programming, vol. 10. MIT press, Massachusetts (2008)

    Google Scholar 

  9. Xue, J.: Loop Tiling for Parallelism. Springer Science & Business Media, Berlin (2000)

    Book  MATH  Google Scholar 

  10. Leopold, C.: Tight bounds on capacity misses for 3D stencil codes. In: Sloot, P.M.A., Tan, C.J.K., Dongarra, J., Hoekstra, A.G. (eds.) ICCS-ComputSci 2002, Part I. LNCS, vol. 2329, pp. 843–852. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  11. Schäfer, A., Fey, D.: High performance stencil code algorithms for GPGPUs. Procedia Comput. Sci. 4, 2027–2036 (2011)

    Article  Google Scholar 

  12. Maruyama, N., Takayuki, A.: Optimizing stencil computations for NVIDIA Kepler GPUs. In: Proceedings of the 1st International Workshop on High Performance Stencil Computations, Vienna (2014)

    Google Scholar 

  13. You, Y., et al.: Evaluating multi-core, many-core architectures through accelerating the three-dimensional LaxCWendroff correction stencil. Int. J. High Perform. Comput. Appl. 28(3), 301–318 (2014)

    Article  Google Scholar 

  14. Rahman, S.M., Faizur, Q.Y., Apan, Q.: Understanding stencil code performance on multicore architectures. In: Proceedings of the 8th ACM International Conference on Computing Frontiers. ACM (2011)

    Google Scholar 

  15. Wang, Q., et al.: Accelerating embarrassingly parallel algorithm on Intel MIC. In: International Conference on Progress in Informatics and Computing (PIC). IEEE (2014)

    Google Scholar 

  16. Tao, G., et al.: Using the intel many integrated core to accelerate graph traversal. Int. J. High Perform. Comput. Appl. 28(3), 255–266 (2014)

    Article  Google Scholar 

Download references

Acknowledgments

The work described in this paper is partially supported by the project of National Science Foundation of China under grant No.61170046 and No.61402495.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chunjiang Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this paper

Cite this paper

Feng, L., Dong, Y., Li, C., Jiang, H. (2016). High Performance Stencil Computations for Intel\(^{\normalsize \circledR }\) Xeon Phi™ Coprocessor. In: Wu, J., Li, L. (eds) Advanced Computer Architecture. ACA 2016. Communications in Computer and Information Science, vol 626. Springer, Singapore. https://doi.org/10.1007/978-981-10-2209-8_10

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-2209-8_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2208-1

  • Online ISBN: 978-981-10-2209-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics