Skip to main content

Feasibility Study of Molecular Dynamics Kernels Exploitation Using EngineCL

  • Conference paper
  • First Online:
Euro-Par 2021: Parallel Processing Workshops (Euro-Par 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13098))

Included in the following conference series:

Abstract

The ubiquity of heterogeneous systems facilitates the exploitation of scientific problems, such as molecular dynamics simulators, but their highly optimized codes for multi-core HPC architectures complicates porting. In this work, EngineCL is extended to enable efficient co-execution of molecular dynamics kernels. Contributions include support for a new execution core and a hybrid co-execution mode, solving the problems encountered when running only with OpenCL-based technologies. Experimental evaluation shows improvements in all the kernels studied, obtaining on average speedups of up to 1.38 in performance and 1.60 in energy efficiency over the current optimized version.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /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
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bergen, B.K., Daniels, M.G., Weber, P.M.: A hybrid programming model for compressible gas dynamics using OpenCL. In: 2010 39th International Conference on Parallel Processing Workshops, pp. 397–404. IEEE (2010)

    Google Scholar 

  2. Dávila Guzmán, M.A., Nozal, R., Gran Tejero, R., Villarroya-Gaudó, M., Suárez Gracia, D., Bosque, J.L.: Cooperative CPU, GPU, and FPGA heterogeneous execution with EngineCL. J. Supercomput. 75(3), 1732–1746 (2019). https://doi.org/10.1007/s11227-019-02768-y

    Article  Google Scholar 

  3. Ding, H., Huang, M.: A unified OpenCL-flavor programming model with scalable hybrid hardware platform on FPGAs. In: 2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig14), pp. 1–7. IEEE (2014)

    Google Scholar 

  4. Gummaraju, J., Sander, B., Morichetti, L., Gaster, B.R., Houston, M., Zheng, B.: Twin peaks: a software platform for heterogeneous computing on general-purpose and graphics processors. In: 2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 205–215. IEEE (2010)

    Google Scholar 

  5. Hofmann, M., Kiesel, R., Leichsenring, D., Rünger, G.: A hybrid CPU/GPU implementation of computationally intensive particle simulations using OpenCL. In: 17th IEEE International Symposium on Parallel and Distributed Computing, pp. 9–16 (2018)

    Google Scholar 

  6. LaKomski, D., Zong, Z., Jin, T., Ge, R.: Optimal balance between energy and performance in hybrid computing applications. In: 2015 Sixth International Green and Sustainable Computing Conference (IGSC), pp. 1–8. IEEE (2015)

    Google Scholar 

  7. Luk, C.K., Hong, S., Kim, H.: Qilin: exploiting parallelism on heterogeneous multiprocessors with adaptive mapping. In: 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), pp. 45–55. IEEE (2009)

    Google Scholar 

  8. Moreton-Fernandez, A., Gonzalez-Escribano, A., Llanos, D.R.: Multi-device controllers: a library to simplify parallel heterogeneous programming. Int. J. Parallel Prog. 47(1), 94–113 (2019)

    Article  Google Scholar 

  9. Nozal, R., Bosque, J.L., Beivide, R.: Towards co-execution on commodity heterogeneous systems: optimizations for time-constrained scenarios. In: 17th International Conference on High Performance Computing & Simulation, HPCS, Ireland, pp. 628–635. IEEE (2019). https://doi.org/10.1109/HPCS48598.2019.9188188

  10. Nozal, R., Bosque, J.L., Beivide, R.: EngineCL: usability and performance in heterogeneous computing. Future Gen. Comp. Syst. 107(C), 522–537 (2020). https://doi.org/10.1016/j.future.2020.02.016

    Article  Google Scholar 

  11. Nozal, R.: Optimizing performance and energy efficiency in massively parallel systems. Universidad de Cantabria (2022)

    Google Scholar 

  12. Ravi, V., Ma, W., Chiu, D., Agrawal, G.: Compiler and runtime support for enabling generalized reduction computations on heterogeneous parallel configurations. In: Proceedings of the 2010 24th ACM International Conference on Supercomputing, pp. 137–146 (2010)

    Google Scholar 

  13. Scogland, T., Rountree, B., Feng, W.C., De Supinski, B.R.: Heterogeneous task scheduling for accelerated OpenMP. In: 2012 IEEE 26th International Parallel and Distributed Processing Symposium, pp. 144–155 (2012)

    Google Scholar 

  14. Seckler, S., Gratl, F., Heinen, M., Vrabec, J., Bungartz, H.J., Neumann, P.: AutoPas in ls1 mardyn: massively parallel particle simulations with node-level auto-tuning. J. Comput. Sci. 50, 101296 (2021). https://doi.org/10.1016/j.jocs.2020.101296

    Article  MathSciNet  Google Scholar 

  15. Seckler, S., Tchipev, N., Bungartz, H.J., Neumann, P.: Load balancing for molecular dynamics simulations on heterogeneous architectures. In: IEEE 23rd International Conference on High Performance Computing (HiPC), pp. 101–110 (2016). https://doi.org/10.1109/HiPC.2016.021

Download references

Acknowledgments

The work has been performed under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC Research Innovation Action under the H2020 Programme; in particular, the author gratefully acknowledges the support of the SPMT Department of the HLRS. Moreover, this work has also been supported by the Spanish Ministry of Education (FPU16/ 03299 grant), the Spanish Science and Technology Commission under contract PID2019-105660RB-C22 and the European HiPEAC Network of Excellence.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Raúl Nozal , Christoph Niethammer , Jose Gracia or Jose Luis Bosque .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nozal, R., Niethammer, C., Gracia, J., Bosque, J.L. (2022). Feasibility Study of Molecular Dynamics Kernels Exploitation Using EngineCL. In: Chaves, R., et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham. https://doi.org/10.1007/978-3-031-06156-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06156-1_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06155-4

  • Online ISBN: 978-3-031-06156-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics