Introduction

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

Publications

  1. GeNN: a code generation framework for accelerated brain simulations.
    Cite this
    Yavuz E, Turner J, Nowotny T, 2016-01-01 - Scientific reports

Credits

  1. Esin Yavuz
    Developer

    Centre for Computational Neuroscience and Robotics, School of Engineering and Informatics

  2. James Turner
    Developer

    Centre for Computational Neuroscience and Robotics, School of Engineering and Informatics

  3. Thomas Nowotny
    Investigator

    Centre for Computational Neuroscience and Robotics, School of Engineering and Informatics

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Summary
AccessionBT000475
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Submitted ByThomas Nowotny