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CoreNEURON : An Optimized Compute Engine for the NEURON Simulator.

Pramod Kumbhar1, Michael Hines2, Jeremy Fouriaux1

  • 1Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.

Frontiers in Neuroinformatics
|October 17, 2019
PubMed
Summary
This summary is machine-generated.

CoreNEURON optimizes the NEURON simulator for new supercomputers. This library significantly reduces memory usage and execution time for neuronal network simulations, improving computational efficiency.

Keywords:
NEURONneuronal networksperformance optimizationsimulationsupercomputing

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Area of Science:

  • Computational Neuroscience
  • High-Performance Computing

Background:

  • The NEURON simulator is a widely used tool for modeling neuronal networks.
  • Large-scale simulations require substantial supercomputing resources (millions of core hours).
  • Evolving supercomputer architectures necessitate optimized simulation software for performance gains.

Purpose of the Study:

  • To adapt the NEURON simulator for next-generation computing architectures.
  • To improve the efficiency of large-scale neuronal network simulations.
  • To present the CoreNEURON library, an optimized compute engine for NEURON.

Main Methods:

  • Extracting and optimizing the NEURON simulator's compute engine into the CoreNEURON library.
  • Integrating CoreNEURON as a library within the NEURON environment.
  • Benchmarking CoreNEURON's performance on diverse hardware (IBM BlueGene/Q, Intel Skylake, Intel MIC, NVIDIA GPU).

Main Results:

  • CoreNEURON achieves 4-7x less memory usage compared to standard NEURON simulations.
  • CoreNEURON demonstrates 2-7x less execution time across various architectures.
  • Maintained binary result compatibility with the original NEURON simulator.

Conclusions:

  • CoreNEURON effectively optimizes NEURON simulations for modern hardware.
  • The library offers substantial improvements in memory and speed for computational neuroscience.
  • CoreNEURON enables more efficient utilization of supercomputing resources for neuronal network modeling.