Large Scale Biologically Realistic Models of Cortical Microcircuit Dynamics with Application to Novel Statistical Classifiers (Pilot Investigation)

Abstract

The purpose of this project was to better understand brain-like network dynamics by incorporated biological parameters into large-scale computer simulations using parallel distributed "Beowulf" clustering. Milestones included improved single- processor efficiency of 24-fold. On multiprocessor clusters, initial time trials on - networks of 2 to 1000 cells suggests that the total time does not depend as heavily on the product (connection probability) x (N cells)squared, but shows a substantial * linear term. The projected time to run a 1-million cell simulation would be about 5.6 days on a single CPU, or roughly 6 hours on the proposed 30-CPU Beowulf system. Substantial progress was made toward a C++ implementation for subsequent research.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 2000
Accession Number
ADA377894

Entities

People

  • Henry Markram
  • Philip H. Goodman
  • Sushil J. Louis

Organizations

  • University of Nevada, Reno

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Automated Target Recognition
  • Brain
  • Classification
  • Computational Neuroscience
  • Computer Programming
  • Computer Simulations
  • Computers
  • Dynamics
  • Language
  • Machine Learning
  • Microcircuits
  • Networks
  • Probability
  • Simulations
  • Simulators
  • Target Recognition

Readers

  • Mathematics or Statistics
  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.

Technology Areas

  • Microelectronics