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From Knights Corner to Landing: A Case Study Based on a Hodgkin-Huxley Neuron Simulator

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High Performance Computing (ISC High Performance 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10524))

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Abstract

Brain modeling has been presenting significant challenges to the world of high-performance computing (HPC) over the years. The field of computational neuroscience has been developing a demand for physiologically plausible neuron models, that feature increased complexity and thus, require greater computational power. We explore Intel’s newest generation of Xeon Phi computing platforms, named Knights Landing (KNL), as a way to match the need for processing power and as an upgrade over the previous generation of Xeon Phi models, the Knights Corner (KNC). Our neuron simulator of choice features a Hodgkin-Huxley-based (HH) model which has been ported on both generations of Xeon Phi platforms and aggressively draws on both platforms’ computational assets. The application uses the OpenMP interface for efficient parallelization and the Xeon Phi’s vectorization buffers for Single-Instruction Multiple Data (SIMD) processing. In this study we offer insight into the efficiency with which the application utilizes the assets of the two Xeon Phi generations and we evaluate the merits of utilizing the KNL over its predecessor. In our case, an out-of-the-box transition on Knights Landing, offers on average 2.4\(\times \) speed up while consuming 48% less energy than KNC.

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Acknowledgments

This work is partially supported by European Commission project H2020–687628–VINEYARD.

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Authors and Affiliations

  1. Microprocessors and Digital Systems Lab, National Technical University of Athens, Athens, Greece

    George Chatzikonstantis, Harry Sidiropoulos & Dimitrios Soudris

  2. Advanced Computing Laboratory, Costa Rica National High Technology Center, San José, Costa Rica

    Diego Jiménez & Esteban Meneses

  3. School of Computing, Costa Rica Institute of Technology, Cartago, Costa Rica

    Esteban Meneses

  4. Neuroscience Department, Erasmus Medical Center Rotterdam, Rotterdam, Netherlands

    Christos Strydis

Authors
  1. George Chatzikonstantis
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  2. Diego Jiménez
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  3. Esteban Meneses
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  4. Christos Strydis
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  5. Harry Sidiropoulos
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  6. Dimitrios Soudris
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Corresponding author

Correspondence to George Chatzikonstantis .

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Editors and Affiliations

  1. Deutsches Klimarechenzentrum (DKRZ), Hamburg, Hamburg, Germany

    Julian M. Kunkel

  2. TITECH, Tokyo, Japan

    Rio Yokota

  3. Department of Computer Science, University of Delaware, Newark, Delaware, USA

    Michela Taufer

  4. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    John Shalf

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Chatzikonstantis, G., Jiménez, D., Meneses, E., Strydis, C., Sidiropoulos, H., Soudris, D. (2017). From Knights Corner to Landing: A Case Study Based on a Hodgkin-Huxley Neuron Simulator. In: Kunkel, J., Yokota, R., Taufer, M., Shalf, J. (eds) High Performance Computing. ISC High Performance 2017. Lecture Notes in Computer Science(), vol 10524. Springer, Cham. https://doi.org/10.1007/978-3-319-67630-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-67630-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67629-6

  • Online ISBN: 978-3-319-67630-2

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