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Performance Analysis of Computational Neuroscience Software NEURON on Knights Corner Many Core Processors

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Book cover Software Challenges to Exascale Computing (SCEC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 964))

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Abstract

In this paper we analyze the performance of the computational neuroscience tool NEURON on Intel Knights Corner processors. Knights Corner was the many core processor that was followed by Knights Landing processors. NEURON is a widely used simulation environment for modeling individual neurons and network of neurons. NEURON is used to simulate large models requiring high performance computing, and understanding performance of NEURON on many core processors is of interest to the neuroscience community, as well as to the high performance computing community. NEURON supports parallelization using Message Passing Interface (MPI) library. Parallel performance of NEURON has been analyzed on various types of high performance resources. We analyze the performance and load balance of NEURON for two different size problems on Knights Corner. We use the TAU and Vampir tool to analyze load imbalance issues of these runs. We compare performance on the host SandyBridge processors of Knights Corner versus on the Many Integrated Core (MIC) cores of Knights Corner.

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References

  1. Carnevale, T., Hines, M.: The NEURON Book. Cambridge University Press, Cambridge (2006)

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  12. https://vampir.eu/

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Acknowledgement

Authors would like to thank Intel IPCC grant and the European Human Brain Project for providing partial funding for this work.

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Authors and Affiliations

  1. San Diego Supercomputer Center, University of California San Diego, San Diego, CA, 92039, USA

    Subhashini Sivagnanam, Kenneth Yoshimoto & Amit Majumdar

  2. Ecole Polytechnique Fédérale de Lausanne, 1015, Laussanne, Switzerland

    Pramod S. Kumbhar

  3. Neuroscience Department, Yale University, New Haven, CT, 06520, USA

    Michael Hines & Ted Carnevale

Authors
  1. Pramod S. Kumbhar
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  2. Subhashini Sivagnanam
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  3. Kenneth Yoshimoto
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  4. Michael Hines
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  5. Ted Carnevale
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  6. Amit Majumdar
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Corresponding author

Correspondence to Amit Majumdar .

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Editors and Affiliations

  1. San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, USA

    Amit Majumdar

  2. Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX, USA

    Ritu Arora

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© 2019 Springer Nature Singapore Pte Ltd.

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Kumbhar, P.S., Sivagnanam, S., Yoshimoto, K., Hines, M., Carnevale, T., Majumdar, A. (2019). Performance Analysis of Computational Neuroscience Software NEURON on Knights Corner Many Core Processors. In: Majumdar, A., Arora, R. (eds) Software Challenges to Exascale Computing. SCEC 2018. Communications in Computer and Information Science, vol 964. Springer, Singapore. https://doi.org/10.1007/978-981-13-7729-7_5

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  • DOI: https://doi.org/10.1007/978-981-13-7729-7_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7728-0

  • Online ISBN: 978-981-13-7729-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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