Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

PLoS One. 2016 Jan 11;11(1):e0146581. doi: 10.1371/journal.pone.0146581. eCollection 2016.

Abstract

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules' local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly's entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel's model integration by combining independently developed models of the retina and lamina neuropils in the fly's visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel's ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel's communication performance both over the number of interface ports exposed by an emulation's constituent modules and the total number of modules comprised by an emulation.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Animals
  • Brain / physiology
  • Brain Mapping / methods
  • Computational Biology / methods
  • Computer Graphics
  • Computer Simulation
  • Drosophila melanogaster / anatomy & histology*
  • Drosophila melanogaster / physiology
  • Neurons / metabolism
  • Programming Languages
  • Retina / physiology
  • Software*

Grant support

This work was supported by Air Force Office of Scientific Research (AFOSR) (http://www.wpafb.af.mil/afrl/afosr/), AFOSR grant #FA9550-12-10232 (author: AAL); National Science Foundation (NSF) (http://www.nsf.gov), NSF grant #1544383 (author: AAL); and Professional Scholarship of the Engineering Graduate Student Council at Columbia University (http://engineering.columbia.edu) (author: LEG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.