Literature DB >> 26539076

Benchmarking neuromorphic systems with Nengo.

Trevor Bekolay1, Terrence C Stewart1, Chris Eliasmith1.   

Abstract

Nengo is a software package for designing and simulating large-scale neural models. Nengo is architected such that the same Nengo model can be simulated on any of several Nengo backends with few to no modifications. Backends translate a model to specific platforms, which include GPUs and neuromorphic hardware. Nengo also contains a large test suite that can be run with any backend and focuses primarily on functional performance. We propose that Nengo's large test suite can be used to benchmark neuromorphic hardware's functional performance and simulation speed in an efficient, unbiased, and future-proof manner. We implement four benchmark models and show that Nengo can collect metrics across five different backends that identify situations in which some backends perform more accurately or quickly.

Entities:  

Keywords:  Nengo; benchmarking; large-scale neural networks; neuromorphic hardware; spiking neural networks

Year:  2015        PMID: 26539076      PMCID: PMC4609756          DOI: 10.3389/fnins.2015.00380

Source DB:  PubMed          Journal:  Front Neurosci        ISSN: 1662-453X            Impact factor:   4.677


  9 in total

1.  OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems.

Authors:  John E Stone; David Gohara; Guochun Shi
Journal:  Comput Sci Eng       Date:  2010-05       Impact factor: 2.080

2.  A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.

Authors:  Daniel Brüderle; Mihai A Petrovici; Bernhard Vogginger; Matthias Ehrlich; Thomas Pfeil; Sebastian Millner; Andreas Grübl; Karsten Wendt; Eric Müller; Marc-Olivier Schwartz; Dan Husmann de Oliveira; Sebastian Jeltsch; Johannes Fieres; Moritz Schilling; Paul Müller; Oliver Breitwieser; Venelin Petkov; Lyle Muller; Andrew P Davison; Pradeep Krishnamurthy; Jens Kremkow; Mikael Lundqvist; Eilif Muller; Johannes Partzsch; Stefan Scholze; Lukas Zühl; Christian Mayr; Alain Destexhe; Markus Diesmann; Tobias C Potjans; Anders Lansner; René Schüffny; Johannes Schemmel; Karlheinz Meier
Journal:  Biol Cybern       Date:  2011-05-27       Impact factor: 2.086

3.  A large-scale model of the functioning brain.

Authors:  Chris Eliasmith; Terrence C Stewart; Xuan Choo; Trevor Bekolay; Travis DeWolf; Yichuan Tang; Charlie Tang; Daniel Rasmussen
Journal:  Science       Date:  2012-11-30       Impact factor: 47.728

4.  Neural control of locomotion; The central pattern generator from cats to humans.

Authors: 
Journal:  Gait Posture       Date:  1998-03-01       Impact factor: 2.840

5.  Learning to select actions with spiking neurons in the Basal Ganglia.

Authors:  Terrence C Stewart; Trevor Bekolay; Chris Eliasmith
Journal:  Front Neurosci       Date:  2012-01-31       Impact factor: 4.677

6.  PyNN: A Common Interface for Neuronal Network Simulators.

Authors:  Andrew P Davison; Daniel Brüderle; Jochen Eppler; Jens Kremkow; Eilif Muller; Dejan Pecevski; Laurent Perrinet; Pierre Yger
Journal:  Front Neuroinform       Date:  2009-01-27       Impact factor: 4.081

7.  Topographica: Building and Analyzing Map-Level Simulations from Python, C/C++, MATLAB, NEST, or NEURON Components.

Authors:  James A Bednar
Journal:  Front Neuroinform       Date:  2009-03-24       Impact factor: 4.081

8.  Brian: a simulator for spiking neural networks in python.

Authors:  Dan Goodman; Romain Brette
Journal:  Front Neuroinform       Date:  2008-11-18       Impact factor: 4.081

9.  Nengo: a Python tool for building large-scale functional brain models.

Authors:  Trevor Bekolay; James Bergstra; Eric Hunsberger; Travis Dewolf; Terrence C Stewart; Daniel Rasmussen; Xuan Choo; Aaron Russell Voelker; Chris Eliasmith
Journal:  Front Neuroinform       Date:  2014-01-06       Impact factor: 4.081

  9 in total

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