Skip to main content

Exploiting and Evaluating OpenSHMEM on KNL Architecture

  • Conference paper
  • First Online:
OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence (OpenSHMEM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10679))

Included in the following conference series:

  • 478 Accesses

Abstract

Manycore processors such as Intel Xeon Phi (KNL) with on-package Multi-Channel DRAM (MCDRAM) are making a paradigm shift in the High Performance Computing (HPC) industry. PGAS programming models such as OpenSHMEM due to its lightweight synchronization primitives and shared memory abstractions are considered a good fit for irregular communication patterns. While regular programming models such as MPI/OpenMP have started utilizing systems with KNL processors, it is still not clear whether PGAS models can easily adopt and fully utilize such systems. In this paper, we conduct a comprehensive performance evaluation of the OpenSHMEM runtime on many-/multi-core processors. We also explore the performance benefits offered by the highly multithreaded KNL along with the AVX-512 extensions and MCDRAM for OpenSHMEM programming model. We evaluate Intra- and Inter-node performance of OpenSHMEM primitives on different application kernels. Our evaluation of application kernels such as NAS Parallel Benchmark and 3D-Stencil kernels show that OpenSHMEM with MVPAICH2-X runtime is able to take advantage of AVX-512 extensions and MCDRAM to exploit the architectural features provided by KNL processors.

This research is supported in part by National Science Foundation grants #CNS-1419123, #CNS-1513120, #ACI-1450440 and #CCF-1565414.

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 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 60.00
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. OSU Micro-Benchmarks (2015)

    Google Scholar 

  2. TACC Stampede KNL Cluster (2017). https://portal.tacc.utexas.edu/user-guides/stampede

  3. Barnes, T., Cook, B., Deslippe, J., Doerfler, D., Friesen, B., He, Y., Kurth, T., Koskela, T., Lobet, M., Malas, T., et al.: Evaluating and optimizing the NERSC workload on knights landing. In: International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), pp. 43–53. IEEE (2016)

    Google Scholar 

  4. Cantalupo, C., Venkatesan, V., Hammond, J., Czurlyo, K., Hammond, S.D.: Memkind: An Extensible Heap Memory Manager for Heterogeneous Memory Platforms and Mixed Memory Policies. Technical report, Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States) (2015)

    Google Scholar 

  5. Cong, G., Almasi, G., Saraswat, V.: Fast PGAS implementation of distributed graph algorithms. In: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2010, pp. 1–11. IEEE Computer Society, Washington, DC (2010)

    Google Scholar 

  6. Doerfler, D., Deslippe, J., Williams, S., Oliker, L., Cook, B., Kurth, T., Lobet, M., Malas, T., Vay, J.-L., Vincenti, H.: Applying the roofline performance model to the intel xeon phi knights landing processor. In: Intel Xeon Phi User’s Group (IXPUG 2016) (2016)

    Google Scholar 

  7. Kandalla, K., Mendygral, P., Radcliffe, N., Cernohous, B., Knaak, D., McMahon, K., Pagel, M.: Optimizing Cray MPI and SHMEM Software Stacks for Cray-XC Supercomputers based on Intel KNL Processors (2016)

    Google Scholar 

  8. Lin, J., Hamidouche, K., Zhang, J., Lu, X., Vishnu, A., Panda, D.: Accelerating k-NN algorithm with hybrid MPI and OpenSHMEM. In: Gorentla Venkata, M., Shamis, P., Imam, N., Lopez, M.G. (eds.) OpenSHMEM 2014. LNCS, vol. 9397, pp. 164–177. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26428-8_11

    Chapter  Google Scholar 

  9. Memory Latency on the Intel Xeon Phi x200 Knights Landing processor. https://sites.utexas.edu/jdm4372/2016/12/06/memory-latency-on-the-intel-xeon-phi-x200-knights-landing-processor/

  10. Potluri, S., Venkatesh, A., Bureddy, D., Kandalla, K., Panda, D.K.: Efficient intra-node communication on intel-MIC clusters. In: 13th IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2013) (2013)

    Google Scholar 

  11. Zhang, J., Behzad, B., Snir, M.: Optimizing the Barnes-Hut algorithm in UPC. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2011, pp. 75:1–75:11. ACM, New York (2011)

    Google Scholar 

  12. Zhao, Z., Marsman, M.: Estimating the performance impact of the MCDRAM on KNL using dual-socket Ivy bridge nodes on Cray XC30. In: Cray User Group Meeting (CUG 2016) (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jahanzeb Maqbool Hashmi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hashmi, J.M., Li, M., Subramoni, H., Panda, D.K. (2018). Exploiting and Evaluating OpenSHMEM on KNL Architecture. In: Gorentla Venkata, M., Imam, N., Pophale, S. (eds) OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence. OpenSHMEM 2017. Lecture Notes in Computer Science(), vol 10679. Springer, Cham. https://doi.org/10.1007/978-3-319-73814-7_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73814-7_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73813-0

  • Online ISBN: 978-3-319-73814-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics