GeNN: a code generation framework for accelerated brain simulations

Yavuz, Esin, Turner, James and Nowotny, Thomas (2016) GeNN: a code generation framework for accelerated brain simulations. Scientific Reports, 6. p. 18854. ISSN 2045-2322

This is the latest version of this item.

[img] PDF (Accepted Manuscript (Scientific Reports)) - Accepted Version
Restricted to SRO admin only

Download (1MB)
[img] PDF - Published Version
Available under License Creative Commons Attribution.

Download (1MB)

Abstract

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/.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science > QA Mathematics > QA0076 Computer software
Depositing User: Esin Yavuz
Date Deposited: 21 Jan 2016 15:46
Last Modified: 22 Aug 2017 09:51
URI: http://sro.sussex.ac.uk/id/eprint/59372

Available Versions of this Item

View download statistics for this item

📧 Request an update
Project NameSussex Project NumberFunderFunder Ref
Green brainG0924EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/J019690/1